Contents
Berkeley
PyTorch Tutorial • Jan 6, 2021
Coursera
Logistic Regression with a Neural Network mindset • May 11, 2022
Custom Layers in Tensorflow 2 • Feb 8, 2022
Custom Loss Function in Tensorflow 2. • Feb 8, 2022
Practice with the Tensorflow 2 Functional API. • Feb 5, 2022
VAE for the CelebA dataset • Sep 14, 2021
KL Divergence Layers • Sep 14, 2021
Maximizing the ELBO • Sep 14, 2021
Minimizing Kullback-Leibler Divergence • Sep 13, 2021
Encoders and decoders • Sep 13, 2021
RealNVP for the LSUN bedroom dataset • Sep 8, 2021
AutoRegressive flows and RealNVP • Sep 8, 2021
Subclassing Bijectors • Sep 7, 2021
The TransformedDistribution class • Sep 7, 2021
Bijectors • Aug 30, 2021
Bayesian Convolutional Neural Network • Aug 26, 2021
Reparameterization layers • Aug 24, 2021
DenseVariational Layers • Aug 24, 2021
Probabilistic Layers • Aug 23, 2021
The DistributionLambda Layer • Aug 19, 2021
Maximum Likelihood Estimation - how neural networks learn • Aug 19, 2021
Trainable Distributions • Aug 18, 2021
Naive Bayes and logistic regression • Aug 18, 2021
Sampling and log probs • Aug 13, 2021
Broadcasting Rules in Tensorflow Probability • Aug 13, 2021
Independent Distribution • Aug 12, 2021
Univariate Distribution • Aug 11, 2021
Multivariate Distribution • Aug 11, 2021
Data_Science
Counting • Sep 9, 2020
Sets • Sep 2, 2020
Introduction to Probability and Statistics • Aug 30, 2020
The Hottest Topics in Machine Learning • Aug 24, 2020
Disney Movies and Box Office Success • Aug 23, 2020
Analyze Your Runkeeper Fitness Data • Aug 22, 2020
Who's Tweeting? Trump or Trudeau? • Aug 21, 2020
Up and Down With the Kardashians • Aug 20, 2020
Comparing Cosmetics by Ingredients • Aug 19, 2020
Exploring 67 years of LEGO • Aug 17, 2020
Exploring the Bitcoin Cryptocurrency Market • Aug 13, 2020
Putting it all together - a case study • May 28, 2020
Introduction to hypothesis testing • May 28, 2020
Bootstrap confidence intervals • May 27, 2020
Parameter estimation by optimization • May 27, 2020
Thinking probabilistically - Continuous variables • May 26, 2020
Thinking probabilistically - Discrete variables • May 26, 2020
Quantitative exploratory data analysis • May 26, 2020
Graphical exploratory data analysis • May 26, 2020
Analyzing the effect of weather on policing • May 26, 2020
Visual exploratory data analysis • May 25, 2020
Exploring the relationship between gender and policing • May 25, 2020
Preparing the data for analysis • May 25, 2020
Datacamp
Correlation and Experimental Design • Aug 28, 2020
More Distributions and the Central Limit Theorem • Aug 28, 2020
Random Numbers and Probability • Aug 26, 2020
Summary Statistics with Python • Aug 26, 2020
The Hottest Topics in Machine Learning • Aug 24, 2020
Disney Movies and Box Office Success • Aug 23, 2020
Analyze Your Runkeeper Fitness Data • Aug 22, 2020
Who's Tweeting? Trump or Trudeau? • Aug 21, 2020
Up and Down With the Kardashians • Aug 20, 2020
Comparing Cosmetics by Ingredients • Aug 19, 2020
Exploring 67 years of LEGO • Aug 17, 2020
Masks and Filters in Biomedical Image Analysis • Aug 15, 2020
Naive Bees Image Loading and Processing • Aug 14, 2020
Exploring the Bitcoin Cryptocurrency Market • Aug 13, 2020
Exploration in Biomedical Image Analysis • Aug 13, 2020
Modeling • Aug 12, 2020
Feature Engineering • Aug 12, 2020
Dive into the Competition • Aug 12, 2020
Kaggle competitions process • Aug 12, 2020
Ensembles and Pipelines in PySpark • Aug 11, 2020
Regression in PySpark • Aug 11, 2020
Classification in PySpark • Aug 10, 2020
Machine Learning with PySpark - Introduction • Aug 10, 2020
Model tuning and selection in PySpark • Aug 10, 2020
Getting started with machine learning pipelines in PySpark • Aug 9, 2020
Manipulating data in PySpark • Aug 9, 2020
Getting to know PySpark • Aug 7, 2020
Informed Search • Aug 6, 2020
Random Search • Aug 6, 2020
Grid search • Aug 5, 2020
Hyperparameters and Parameters • Aug 5, 2020
Understanding and Improving Deep Convolutional Networks in Keras • Aug 4, 2020
Going Deeper Convolutions in Keras • Aug 4, 2020
Using Convolutions in Keras • Aug 3, 2020
Image Processing With Neural Networks • Aug 3, 2020
Advanced Operations, Detecting Faces and Features • Aug 2, 2020
Image restoration, Noise, Segmentation and Contours • Aug 2, 2020
Filters, Contrast, Transformation and Morphology • Aug 2, 2020
Introducing Image Processing and scikit-image • Jul 31, 2020
Using Convolutional Neural Networks in PyTorch • Jul 29, 2020
Convolutional Neural Networks in PyTorch • Jul 29, 2020
Artificial Neural Networks in PyTorch • Jul 28, 2020
Introduction to PyTorch • Jul 28, 2020
Multiple Outputs in Keras • Jul 28, 2020
Multiple Inputs in Keras • Jul 28, 2020
Two Input Networks Using Categorical Embeddings, Shared Layers, and Merge Layers • Jul 27, 2020
The Keras Functional API • Jul 27, 2020
Advanced Model Architectures • Jul 26, 2020
Improving Your Model Performance • Jul 23, 2020
Going Deeper • Jul 23, 2020
Introducing Keras • Jul 22, 2020
Fine-tuning keras models • Jul 21, 2020
Building deep learning models with keras • Jul 21, 2020
Optimizing a neural network with backward propagation • Jul 21, 2020
Basics of deep learning and neural networks • Jul 21, 2020
High Level APIs • Jul 20, 2020
Neural Networks • Jul 20, 2020
Linear models • Jul 19, 2020
Introduction to TensorFlow • Jul 18, 2020
TF-IDF and similarity scores • Jul 17, 2020
N-Gram models • Jul 17, 2020
Text preprocessing, POS tagging and NER • Jul 17, 2020
Basic features and readability scores • Jul 17, 2020
Building a fake news classifier • Jul 16, 2020
Named-entity recognition • Jul 16, 2020
Simple topic identification • Jul 15, 2020
Regular expressions and word tokenization • Jul 15, 2020
Selecting the best model with Hyperparameter tuning. • Jul 14, 2020
Cross Validation • Jul 14, 2020
Validation Basics • Jul 13, 2020
Basic Modeling in scikit-learn • Jul 13, 2020
Dealing with Text Data • Jul 12, 2020
Conforming to Statistical Assumptions • Jul 12, 2020
Dealing with Messy Data • Jul 12, 2020
Creating Features • Jul 12, 2020
Preprocessing - Putting it all together • Jul 10, 2020
Selecting features for modeling • Jul 10, 2020
Feature Engineering • Jul 9, 2020
Standardizing Data • Jul 9, 2020
Introduction to Data Preprocessing • Jul 9, 2020
Feature extraction • Jul 9, 2020
Feature selection II - selecting for model accuracy • Jul 8, 2020
Feature selection I - selecting for feature information • Jul 8, 2020
Exploring high dimensional data • Jul 8, 2020
Using XGBoost in pipelines • Jul 7, 2020
Fine-tuning your XGBoost model • Jul 7, 2020
Regression with XGBoost • Jul 7, 2020
Classification with XGBoost • Jul 6, 2020
Support Vector Machines • Jul 6, 2020
Logistic regression • Jul 6, 2020
Loss functions • Jul 5, 2020
Applying logistic regression and SVM • Jul 5, 2020
Creating a choropleth building permit density in Nashville • Jul 3, 2020
GeoSeries and folium • Jul 2, 2020
Creating and joining GeoDataFrames • Jul 1, 2020
Building 2-layer maps - combining polygons and scatterplots • Jul 1, 2020
Layouts, Interactions, and Annotations • Jun 30, 2020
Basic plotting with Bokeh • Jun 30, 2020
Visualization in the data science workflow • Jun 30, 2020
Showing uncertainty • Jun 29, 2020
Using color in your visualizations • Jun 28, 2020
Customizing Seaborn Plots • Jun 27, 2020
Visualizing a Categorical and a Quantitative Variable • Jun 26, 2020
Visualizing Two Quantitative Variables • Jun 26, 2020
Introduction to Seaborn • Jun 26, 2020
Highlighting your data • Jun 26, 2020
Sharing visualizations with others • Jun 26, 2020
Quantitative comparisons and statistical visualizations • Jun 26, 2020
Plotting time-series • Jun 26, 2020
Introduction to Matplotlib • Jun 26, 2020
Earthquakes and oil mining in Oklahoma • Jun 24, 2020
Statistical seismology and the Parkfield region • Jun 24, 2020
The Current Controversy of the 2013 World Championships • Jun 24, 2020
Analysis of results of the 2015 FINA World Swimming Championships • Jun 23, 2020
Fish sleep and bacteria growth - A review of Statistical Thinking I and II • Jun 23, 2020
Advanced Applications of Simulation • Jun 22, 2020
Resampling methods • Jun 22, 2020
Probability and data generation process • Jun 21, 2020
Basics of randomness and simulation • Jun 21, 2020
Estimating Model Parameters • Jun 21, 2020
Making Model Predictions • Jun 20, 2020
Building Linear Models • Jun 19, 2020
Exploring Linear Trends • Jun 19, 2020
Validating and Inspecting Time Series Models • Jun 18, 2020
Predicting Time Series Data • Jun 18, 2020
Time Series as Inputs to a Model • Jun 17, 2020
Time Series and Machine Learning Primer • Jun 17, 2020
Seasonal ARIMA Models • Jun 16, 2020
The Best of the Best Models • Jun 16, 2020
Fitting the Future with time series analysis • Jun 15, 2020
ARMA Models • Jun 15, 2020
Case Study in time series analysis • Jun 14, 2020
Work with Multiple Time Series • Jun 13, 2020
Seasonality, Trend and Noise • Jun 13, 2020
Summary Statistics and Diagnostics • Jun 12, 2020
Introduction of visualization in time series analysis • Jun 12, 2020
Putting it all together - Building a value-weighted index • Jun 12, 2020
Window Functions - Rolling and Expanding Metrics • Jun 11, 2020
Basic Time Series Metrics & Resampling • Jun 10, 2020
Working with Time Series in Pandas • Jun 9, 2020
Putting It All Together • Jun 9, 2020
Moving Average (MA) and ARMA Models • Jun 8, 2020
Autoregressive (AR) Models • Jun 8, 2020
Some Simple Time Series • Jun 7, 2020
Correlation and Autocorrelation • Jun 7, 2020
Clustering in Real World • Jun 6, 2020
K-Means Clustering • Jun 6, 2020
Hierarchical Clustering • Jun 6, 2020
Introduction to Clustering • Jun 6, 2020
School Budgeting with Machine Learning in Python • Jun 5, 2020
Model Tuning • Jun 4, 2020
Boosting • Jun 4, 2020
Bagging and Random Forests • Jun 4, 2020
The Bias-Variance Tradeoff • Jun 3, 2020
Decision tree for classification • Jun 3, 2020
Discovering interpretable features • Jun 2, 2020
Decorrelating your data and dimension reduction • Jun 2, 2020
Visualization with hierarchical clustering and t-SNE • Jun 1, 2020
Clustering for dataset exploration • Jun 1, 2020
Predicting Credit Card Approvals • May 31, 2020
Preprocessing and pipelines • May 31, 2020
Fine-tuning your model • May 30, 2020
Regression • May 29, 2020
Classification • May 29, 2020
Dr. Semmelweis and the Discovery of Handwashing • May 29, 2020
Putting it all together - a case study • May 28, 2020
Introduction to hypothesis testing • May 28, 2020
Bootstrap confidence intervals • May 27, 2020
Parameter estimation by optimization • May 27, 2020
Thinking probabilistically - Continuous variables • May 26, 2020
Thinking probabilistically - Discrete variables • May 26, 2020
Quantitative exploratory data analysis • May 26, 2020
Graphical exploratory data analysis • May 26, 2020
Analyzing the effect of weather on policing • May 26, 2020
Visual exploratory data analysis • May 25, 2020
Exploring the relationship between gender and policing • May 25, 2020
Preparing the data for analysis • May 25, 2020
Multivariate Thinking • May 24, 2020
Relationships • May 24, 2020
Distributions • May 23, 2020
Read, clean, and validate • May 23, 2020
More on Decorators • May 22, 2020
Decorators • May 22, 2020
Deep_Learning
RNN - Many-to-many bidirectional • Dec 10, 2020
RNN - Many-to-many • Dec 9, 2020
RNN - Many-to-one stacking • Dec 8, 2020
RNN - Many-to-one • Dec 6, 2020
RNN Basic • Oct 26, 2020
Image Classification with Cat and Dog • Oct 16, 2020
Super-Resolution Convolutional Neural Network • Oct 13, 2020
CNN with MNIST dataset • Oct 10, 2020
CNN Basic • Oct 7, 2020
Training Hello world model for Microcontrollers • Sep 24, 2020
Image Classification with Fashion MNIST • Sep 21, 2020
Several Tips for Improving Neural Network • Sep 18, 2020
XOR Problem in Deep Neural Network • Sep 16, 2020
Exploration in Biomedical Image Analysis • Aug 13, 2020
Object Recognition with ALL-CNN • Aug 11, 2020
Understanding and Improving Deep Convolutional Networks in Keras • Aug 4, 2020
Going Deeper Convolutions in Keras • Aug 4, 2020
Using Convolutions in Keras • Aug 3, 2020
Image Processing With Neural Networks • Aug 3, 2020
Using Convolutional Neural Networks in PyTorch • Jul 29, 2020
Convolutional Neural Networks in PyTorch • Jul 29, 2020
Artificial Neural Networks in PyTorch • Jul 28, 2020
Introduction to PyTorch • Jul 28, 2020
Multiple Outputs in Keras • Jul 28, 2020
Multiple Inputs in Keras • Jul 28, 2020
Two Input Networks Using Categorical Embeddings, Shared Layers, and Merge Layers • Jul 27, 2020
The Keras Functional API • Jul 27, 2020
Advanced Model Architectures • Jul 26, 2020
Improving Your Model Performance • Jul 23, 2020
Going Deeper • Jul 23, 2020
Introducing Keras • Jul 22, 2020
Fine-tuning keras models • Jul 21, 2020
Building deep learning models with keras • Jul 21, 2020
Optimizing a neural network with backward propagation • Jul 21, 2020
Basics of deep learning and neural networks • Jul 21, 2020
High Level APIs • Jul 20, 2020
Neural Networks • Jul 20, 2020
Linear models • Jul 19, 2020
Introduction to TensorFlow • Jul 18, 2020
DeepLearning.AI
Logistic Regression with a Neural Network mindset • May 11, 2022
Custom Layers in Tensorflow 2 • Feb 8, 2022
Custom Loss Function in Tensorflow 2. • Feb 8, 2022
Practice with the Tensorflow 2 Functional API. • Feb 5, 2022
edX
Matplotlib Tutorial • Sep 9, 2020
Counting • Sep 9, 2020
Sets • Sep 2, 2020
Introduction to Probability and Statistics • Aug 30, 2020
Statistical Fallacies • Jun 1, 2020
Machine Learning • May 31, 2020
Grokking_Deep_Reinforcement_Learning
ICL
VAE for the CelebA dataset • Sep 14, 2021
KL Divergence Layers • Sep 14, 2021
Maximizing the ELBO • Sep 14, 2021
Minimizing Kullback-Leibler Divergence • Sep 13, 2021
Encoders and decoders • Sep 13, 2021
RealNVP for the LSUN bedroom dataset • Sep 8, 2021
AutoRegressive flows and RealNVP • Sep 8, 2021
Subclassing Bijectors • Sep 7, 2021
The TransformedDistribution class • Sep 7, 2021
Bijectors • Aug 30, 2021
Bayesian Convolutional Neural Network • Aug 26, 2021
Reparameterization layers • Aug 24, 2021
DenseVariational Layers • Aug 24, 2021
Probabilistic Layers • Aug 23, 2021
The DistributionLambda Layer • Aug 19, 2021
Maximum Likelihood Estimation - how neural networks learn • Aug 19, 2021
Trainable Distributions • Aug 18, 2021
Naive Bayes and logistic regression • Aug 18, 2021
Sampling and log probs • Aug 13, 2021
Broadcasting Rules in Tensorflow Probability • Aug 13, 2021
Independent Distribution • Aug 12, 2021
Univariate Distribution • Aug 11, 2021
Multivariate Distribution • Aug 11, 2021
Orthogonal Projections • Mar 14, 2021
Julia
Exploring data on COVID-19 • Dec 28, 2020
Kaggle
Modeling • Aug 12, 2020
Feature Engineering • Aug 12, 2020
Dive into the Competition • Aug 12, 2020
Kaggle competitions process • Aug 12, 2020
Machine_Learning
Ridge-Lasso Regression • Jun 17, 2021
Likelihood Estimation • Jun 16, 2021
Model Selection • Jun 13, 2021
Linear Discriminant Analysis (LDA) • Jun 9, 2021
Classification Model • May 27, 2021
Linear Regression Model • May 20, 2021
K-Means Clustering for Imagery Analysis • Oct 26, 2020
Text Classification with NLTK • Oct 23, 2020
Introduction to Natural Language Processing • Oct 22, 2020
Causal Graphical Model • Oct 5, 2020
Causal Bayesian Network • Oct 2, 2020
Causality • Oct 1, 2020
Regularized likelihood methods • Sep 14, 2020
Application and Tips for Machine Learning • Sep 11, 2020
Softmax Regression • Sep 10, 2020
Logistic Regression/Classification • Sep 9, 2020
Matrix Decomposition • Sep 8, 2020
Multi-variable Linear Regression • Sep 8, 2020
Cost Minimization using Gradient Descent • Sep 7, 2020
Overview of Sparse Modeling • Sep 7, 2020
Linear models in Deep Neural Networks • Sep 2, 2020
Convexity of Linear Hypothesis and Margin Bound of Linear Classifiers • Sep 1, 2020
Maximum Margin Principle and Soft Margin Hard Margin • Aug 31, 2020
Perceptron and its convergence theorem • Aug 30, 2020
The Hottest Topics in Machine Learning • Aug 24, 2020
Disney Movies and Box Office Success • Aug 23, 2020
Modeling • Aug 12, 2020
Feature Engineering • Aug 12, 2020
Dive into the Competition • Aug 12, 2020
Kaggle competitions process • Aug 12, 2020
Ensembles and Pipelines in PySpark • Aug 11, 2020
Classification in PySpark • Aug 10, 2020
Machine Learning with PySpark - Introduction • Aug 10, 2020
Model tuning and selection in PySpark • Aug 10, 2020
Getting started with machine learning pipelines in PySpark • Aug 9, 2020
Informed Search • Aug 6, 2020
Random Search • Aug 6, 2020
Grid search • Aug 5, 2020
Hyperparameters and Parameters • Aug 5, 2020
DNA Classification • Aug 4, 2020
Diabetes Onset Detection • Aug 4, 2020
Stock Market Clustering with a KMeans algorithm • Aug 2, 2020
Credit Card Fraud Detection • Jul 29, 2020
Board Game Review Prediction • Jul 29, 2020
Breast Cancer Detection with ML • Jul 28, 2020
Selecting the best model with Hyperparameter tuning. • Jul 14, 2020
Cross Validation • Jul 14, 2020
Validation Basics • Jul 13, 2020
Basic Modeling in scikit-learn • Jul 13, 2020
Dealing with Text Data • Jul 12, 2020
Conforming to Statistical Assumptions • Jul 12, 2020
Dealing with Messy Data • Jul 12, 2020
Creating Features • Jul 12, 2020
Preprocessing - Putting it all together • Jul 10, 2020
Selecting features for modeling • Jul 10, 2020
Feature Engineering • Jul 9, 2020
Standardizing Data • Jul 9, 2020
Introduction to Data Preprocessing • Jul 9, 2020
Feature extraction • Jul 9, 2020
Feature selection II - selecting for model accuracy • Jul 8, 2020
Feature selection I - selecting for feature information • Jul 8, 2020
Exploring high dimensional data • Jul 8, 2020
Using XGBoost in pipelines • Jul 7, 2020
Fine-tuning your XGBoost model • Jul 7, 2020
Regression with XGBoost • Jul 7, 2020
Classification with XGBoost • Jul 6, 2020
Support Vector Machines • Jul 6, 2020
Logistic regression • Jul 6, 2020
Loss functions • Jul 5, 2020
Applying logistic regression and SVM • Jul 5, 2020
Validating and Inspecting Time Series Models • Jun 18, 2020
Predicting Time Series Data • Jun 18, 2020
Time Series as Inputs to a Model • Jun 17, 2020
Time Series and Machine Learning Primer • Jun 17, 2020
Clustering in Real World • Jun 6, 2020
K-Means Clustering • Jun 6, 2020
Hierarchical Clustering • Jun 6, 2020
Introduction to Clustering • Jun 6, 2020
School Budgeting with Machine Learning in Python • Jun 5, 2020
Model Tuning • Jun 4, 2020
Boosting • Jun 4, 2020
Bagging and Random Forests • Jun 4, 2020
The Bias-Variance Tradeoff • Jun 3, 2020
Decision tree for classification • Jun 3, 2020
Discovering interpretable features • Jun 2, 2020
Decorrelating your data and dimension reduction • Jun 2, 2020
Visualization with hierarchical clustering and t-SNE • Jun 1, 2020
Clustering for dataset exploration • Jun 1, 2020
Machine Learning • May 31, 2020
Predicting Credit Card Approvals • May 31, 2020
Preprocessing and pipelines • May 31, 2020
Fine-tuning your model • May 30, 2020
Regression • May 29, 2020
Classification • May 29, 2020
Mathematics
Orthogonal Projections • Mar 14, 2021
MIT
Pixels-to-Control Learning • Mar 6, 2021
Debiasing Facial Detection Systems • Feb 27, 2021
Music Generation • Feb 14, 2021
Exploring data on COVID-19 • Dec 28, 2020
Modeling
Advanced Applications of Simulation • Jun 22, 2020
Resampling methods • Jun 22, 2020
Probability and data generation process • Jun 21, 2020
Basics of randomness and simulation • Jun 21, 2020
Estimating Model Parameters • Jun 21, 2020
Making Model Predictions • Jun 20, 2020
Building Linear Models • Jun 19, 2020
Exploring Linear Trends • Jun 19, 2020
Natural_Language_Processing
K-Means Clustering for Imagery Analysis • Oct 26, 2020
Text Classification with NLTK • Oct 23, 2020
Introduction to Natural Language Processing • Oct 22, 2020
TF-IDF and similarity scores • Jul 17, 2020
N-Gram models • Jul 17, 2020
Text preprocessing, POS tagging and NER • Jul 17, 2020
Basic features and readability scores • Jul 17, 2020
Building a fake news classifier • Jul 16, 2020
Named-entity recognition • Jul 16, 2020
Simple topic identification • Jul 15, 2020
Regular expressions and word tokenization • Jul 15, 2020
Probability
Counting • Sep 9, 2020
Sets • Sep 2, 2020
Introduction to Probability and Statistics • Aug 30, 2020
PySpark
Ensembles and Pipelines in PySpark • Aug 11, 2020
Regression in PySpark • Aug 11, 2020
Classification in PySpark • Aug 10, 2020
Machine Learning with PySpark - Introduction • Aug 10, 2020
Model tuning and selection in PySpark • Aug 10, 2020
Getting started with machine learning pipelines in PySpark • Aug 9, 2020
Manipulating data in PySpark • Aug 9, 2020
Getting to know PySpark • Aug 7, 2020
Python
Logistic Regression with a Neural Network mindset • May 11, 2022
Custom Layers in Tensorflow 2 • Feb 8, 2022
Custom Loss Function in Tensorflow 2. • Feb 8, 2022
Practice with the Tensorflow 2 Functional API. • Feb 5, 2022
VAE for the CelebA dataset • Sep 14, 2021
KL Divergence Layers • Sep 14, 2021
Maximizing the ELBO • Sep 14, 2021
Minimizing Kullback-Leibler Divergence • Sep 13, 2021
Encoders and decoders • Sep 13, 2021
RealNVP for the LSUN bedroom dataset • Sep 8, 2021
AutoRegressive flows and RealNVP • Sep 8, 2021
Subclassing Bijectors • Sep 7, 2021
The TransformedDistribution class • Sep 7, 2021
Bijectors • Aug 30, 2021
Bayesian Convolutional Neural Network • Aug 26, 2021
Reparameterization layers • Aug 24, 2021
DenseVariational Layers • Aug 24, 2021
Probabilistic Layers • Aug 23, 2021
The DistributionLambda Layer • Aug 19, 2021
Maximum Likelihood Estimation - how neural networks learn • Aug 19, 2021
Trainable Distributions • Aug 18, 2021
Naive Bayes and logistic regression • Aug 18, 2021
Sampling and log probs • Aug 13, 2021
Broadcasting Rules in Tensorflow Probability • Aug 13, 2021
Independent Distribution • Aug 12, 2021
Univariate Distribution • Aug 11, 2021
Multivariate Distribution • Aug 11, 2021
The Power of Image Augmentation • Jul 30, 2021
Various way of Stock Data Analysis • Jul 28, 2021
Ridge-Lasso Regression • Jun 17, 2021
Likelihood Estimation • Jun 16, 2021
Model Selection • Jun 13, 2021
Linear Discriminant Analysis (LDA) • Jun 9, 2021
Classification Model • May 27, 2021
Linear Regression Model • May 20, 2021
REINFORCE on CartPole-v0 • May 12, 2021
Cross-Entropy Methods (CEM) on MountainCarContinuous-v0 • May 11, 2021
Deep Q-Network (DQN) on LunarLander-v2 • May 7, 2021
Orthogonal Projections • Mar 14, 2021
Pixels-to-Control Learning • Mar 6, 2021
Debiasing Facial Detection Systems • Feb 27, 2021
Music Generation • Feb 14, 2021
PyTorch Tutorial • Jan 6, 2021
RNN - Many-to-many bidirectional • Dec 10, 2020
RNN - Many-to-many • Dec 9, 2020
RNN - Many-to-one stacking • Dec 8, 2020
RNN - Many-to-one • Dec 6, 2020
RNN Basic • Oct 26, 2020
K-Means Clustering for Imagery Analysis • Oct 26, 2020
Text Classification with NLTK • Oct 23, 2020
Introduction to Natural Language Processing • Oct 22, 2020
Image Classification with Cat and Dog • Oct 16, 2020
Super-Resolution Convolutional Neural Network • Oct 13, 2020
CNN with MNIST dataset • Oct 10, 2020
CNN Basic • Oct 7, 2020
Training Hello world model for Microcontrollers • Sep 24, 2020
Image Classification with Fashion MNIST • Sep 21, 2020
Several Tips for Improving Neural Network • Sep 18, 2020
XOR Problem in Deep Neural Network • Sep 16, 2020
Application and Tips for Machine Learning • Sep 11, 2020
Softmax Regression • Sep 10, 2020
Logistic Regression/Classification • Sep 9, 2020
Matplotlib Tutorial • Sep 9, 2020
Counting • Sep 9, 2020
Multi-variable Linear Regression • Sep 8, 2020
Cost Minimization using Gradient Descent • Sep 7, 2020
Simple Linear Regression with Tensorflow • Sep 5, 2020
Sets • Sep 2, 2020
Introduction to Probability and Statistics • Aug 30, 2020
Correlation and Experimental Design • Aug 28, 2020
More Distributions and the Central Limit Theorem • Aug 28, 2020
Random Numbers and Probability • Aug 26, 2020
Summary Statistics with Python • Aug 26, 2020
The Hottest Topics in Machine Learning • Aug 24, 2020
Disney Movies and Box Office Success • Aug 23, 2020
Analyze Your Runkeeper Fitness Data • Aug 22, 2020
Who's Tweeting? Trump or Trudeau? • Aug 21, 2020
Up and Down With the Kardashians • Aug 20, 2020
Comparing Cosmetics by Ingredients • Aug 19, 2020
Exploring 67 years of LEGO • Aug 17, 2020
Masks and Filters in Biomedical Image Analysis • Aug 15, 2020
Naive Bees Image Loading and Processing • Aug 14, 2020
Exploring the Bitcoin Cryptocurrency Market • Aug 13, 2020
Exploration in Biomedical Image Analysis • Aug 13, 2020
Modeling • Aug 12, 2020
Feature Engineering • Aug 12, 2020
Dive into the Competition • Aug 12, 2020
Kaggle competitions process • Aug 12, 2020
Object Recognition with ALL-CNN • Aug 11, 2020
Ensembles and Pipelines in PySpark • Aug 11, 2020
Regression in PySpark • Aug 11, 2020
Classification in PySpark • Aug 10, 2020
Machine Learning with PySpark - Introduction • Aug 10, 2020
Model tuning and selection in PySpark • Aug 10, 2020
Getting started with machine learning pipelines in PySpark • Aug 9, 2020
Manipulating data in PySpark • Aug 9, 2020
Getting to know PySpark • Aug 7, 2020
Policy Gradient with gym-MiniGrid • Aug 6, 2020
Informed Search • Aug 6, 2020
Random Search • Aug 6, 2020
Grid search • Aug 5, 2020
Hyperparameters and Parameters • Aug 5, 2020
DNA Classification • Aug 4, 2020
Understanding and Improving Deep Convolutional Networks in Keras • Aug 4, 2020
Going Deeper Convolutions in Keras • Aug 4, 2020
Diabetes Onset Detection • Aug 4, 2020
Using Convolutions in Keras • Aug 3, 2020
Image Processing With Neural Networks • Aug 3, 2020
Stock Market Clustering with a KMeans algorithm • Aug 2, 2020
Advanced Operations, Detecting Faces and Features • Aug 2, 2020
Image restoration, Noise, Segmentation and Contours • Aug 2, 2020
Filters, Contrast, Transformation and Morphology • Aug 2, 2020
Introducing Image Processing and scikit-image • Jul 31, 2020
Credit Card Fraud Detection • Jul 29, 2020
Board Game Review Prediction • Jul 29, 2020
Using Convolutional Neural Networks in PyTorch • Jul 29, 2020
Convolutional Neural Networks in PyTorch • Jul 29, 2020
Artificial Neural Networks in PyTorch • Jul 28, 2020
Introduction to PyTorch • Jul 28, 2020
Multiple Outputs in Keras • Jul 28, 2020
Multiple Inputs in Keras • Jul 28, 2020
Breast Cancer Detection with ML • Jul 28, 2020
Two Input Networks Using Categorical Embeddings, Shared Layers, and Merge Layers • Jul 27, 2020
The Keras Functional API • Jul 27, 2020
Advanced Model Architectures • Jul 26, 2020
Improving Your Model Performance • Jul 23, 2020
Going Deeper • Jul 23, 2020
Introducing Keras • Jul 22, 2020
Fine-tuning keras models • Jul 21, 2020
Building deep learning models with keras • Jul 21, 2020
Optimizing a neural network with backward propagation • Jul 21, 2020
Basics of deep learning and neural networks • Jul 21, 2020
High Level APIs • Jul 20, 2020
Neural Networks • Jul 20, 2020
Linear models • Jul 19, 2020
Introduction to TensorFlow • Jul 18, 2020
TF-IDF and similarity scores • Jul 17, 2020
N-Gram models • Jul 17, 2020
Text preprocessing, POS tagging and NER • Jul 17, 2020
Basic features and readability scores • Jul 17, 2020
Building a fake news classifier • Jul 16, 2020
Named-entity recognition • Jul 16, 2020
Simple topic identification • Jul 15, 2020
Regular expressions and word tokenization • Jul 15, 2020
Selecting the best model with Hyperparameter tuning. • Jul 14, 2020
Cross Validation • Jul 14, 2020
Validation Basics • Jul 13, 2020
Basic Modeling in scikit-learn • Jul 13, 2020
Dealing with Text Data • Jul 12, 2020
Conforming to Statistical Assumptions • Jul 12, 2020
Dealing with Messy Data • Jul 12, 2020
Creating Features • Jul 12, 2020
Preprocessing - Putting it all together • Jul 10, 2020
Selecting features for modeling • Jul 10, 2020
Feature Engineering • Jul 9, 2020
Standardizing Data • Jul 9, 2020
Introduction to Data Preprocessing • Jul 9, 2020
Feature extraction • Jul 9, 2020
Feature selection II - selecting for model accuracy • Jul 8, 2020
Feature selection I - selecting for feature information • Jul 8, 2020
Exploring high dimensional data • Jul 8, 2020
Using XGBoost in pipelines • Jul 7, 2020
Fine-tuning your XGBoost model • Jul 7, 2020
Regression with XGBoost • Jul 7, 2020
Classification with XGBoost • Jul 6, 2020
Support Vector Machines • Jul 6, 2020
Logistic regression • Jul 6, 2020
Loss functions • Jul 5, 2020
Applying logistic regression and SVM • Jul 5, 2020
Creating a choropleth building permit density in Nashville • Jul 3, 2020
GeoSeries and folium • Jul 2, 2020
Creating and joining GeoDataFrames • Jul 1, 2020
Building 2-layer maps - combining polygons and scatterplots • Jul 1, 2020
Layouts, Interactions, and Annotations • Jun 30, 2020
Basic plotting with Bokeh • Jun 30, 2020
Visualization in the data science workflow • Jun 30, 2020
Showing uncertainty • Jun 29, 2020
Using color in your visualizations • Jun 28, 2020
Customizing Seaborn Plots • Jun 27, 2020
Visualizing a Categorical and a Quantitative Variable • Jun 26, 2020
Visualizing Two Quantitative Variables • Jun 26, 2020
Introduction to Seaborn • Jun 26, 2020
Highlighting your data • Jun 26, 2020
Sharing visualizations with others • Jun 26, 2020
Quantitative comparisons and statistical visualizations • Jun 26, 2020
Plotting time-series • Jun 26, 2020
Introduction to Matplotlib • Jun 26, 2020
Earthquakes and oil mining in Oklahoma • Jun 24, 2020
Statistical seismology and the Parkfield region • Jun 24, 2020
The Current Controversy of the 2013 World Championships • Jun 24, 2020
Analysis of results of the 2015 FINA World Swimming Championships • Jun 23, 2020
Fish sleep and bacteria growth - A review of Statistical Thinking I and II • Jun 23, 2020
Advanced Applications of Simulation • Jun 22, 2020
Resampling methods • Jun 22, 2020
Probability and data generation process • Jun 21, 2020
Basics of randomness and simulation • Jun 21, 2020
Estimating Model Parameters • Jun 21, 2020
Making Model Predictions • Jun 20, 2020
Building Linear Models • Jun 19, 2020
Exploring Linear Trends • Jun 19, 2020
Validating and Inspecting Time Series Models • Jun 18, 2020
Predicting Time Series Data • Jun 18, 2020
Time Series as Inputs to a Model • Jun 17, 2020
Time Series and Machine Learning Primer • Jun 17, 2020
Seasonal ARIMA Models • Jun 16, 2020
The Best of the Best Models • Jun 16, 2020
Fitting the Future with time series analysis • Jun 15, 2020
ARMA Models • Jun 15, 2020
Case Study in time series analysis • Jun 14, 2020
Work with Multiple Time Series • Jun 13, 2020
Seasonality, Trend and Noise • Jun 13, 2020
Summary Statistics and Diagnostics • Jun 12, 2020
Introduction of visualization in time series analysis • Jun 12, 2020
Putting it all together - Building a value-weighted index • Jun 12, 2020
Window Functions - Rolling and Expanding Metrics • Jun 11, 2020
Basic Time Series Metrics & Resampling • Jun 10, 2020
Working with Time Series in Pandas • Jun 9, 2020
Putting It All Together • Jun 9, 2020
Moving Average (MA) and ARMA Models • Jun 8, 2020
Autoregressive (AR) Models • Jun 8, 2020
Some Simple Time Series • Jun 7, 2020
Correlation and Autocorrelation • Jun 7, 2020
Clustering in Real World • Jun 6, 2020
K-Means Clustering • Jun 6, 2020
Hierarchical Clustering • Jun 6, 2020
Introduction to Clustering • Jun 6, 2020
School Budgeting with Machine Learning in Python • Jun 5, 2020
Model Tuning • Jun 4, 2020
Boosting • Jun 4, 2020
Bagging and Random Forests • Jun 4, 2020
The Bias-Variance Tradeoff • Jun 3, 2020
Decision tree for classification • Jun 3, 2020
Discovering interpretable features • Jun 2, 2020
Decorrelating your data and dimension reduction • Jun 2, 2020
Statistical Fallacies • Jun 1, 2020
Visualization with hierarchical clustering and t-SNE • Jun 1, 2020
Clustering for dataset exploration • Jun 1, 2020
Machine Learning • May 31, 2020
Predicting Credit Card Approvals • May 31, 2020
Preprocessing and pipelines • May 31, 2020
Fine-tuning your model • May 30, 2020
Regression • May 29, 2020
Classification • May 29, 2020
Dr. Semmelweis and the Discovery of Handwashing • May 29, 2020
Putting it all together - a case study • May 28, 2020
Introduction to hypothesis testing • May 28, 2020
Bootstrap confidence intervals • May 27, 2020
Parameter estimation by optimization • May 27, 2020
Thinking probabilistically - Continuous variables • May 26, 2020
Thinking probabilistically - Discrete variables • May 26, 2020
Quantitative exploratory data analysis • May 26, 2020
Graphical exploratory data analysis • May 26, 2020
Analyzing the effect of weather on policing • May 26, 2020
Software Engineering Practices, Part 2 • May 25, 2020
Visual exploratory data analysis • May 25, 2020
Exploring the relationship between gender and policing • May 25, 2020
Preparing the data for analysis • May 25, 2020
Multivariate Thinking • May 24, 2020
Relationships • May 24, 2020
Distributions • May 23, 2020
Read, clean, and validate • May 23, 2020
More on Decorators • May 22, 2020
Decorators • May 22, 2020
PyTorch
REINFORCE on CartPole-v0 • May 12, 2021
Cross-Entropy Methods (CEM) on MountainCarContinuous-v0 • May 11, 2021
Deep Q-Network (DQN) on LunarLander-v2 • May 7, 2021
PyTorch Tutorial • Jan 6, 2021
Policy Gradient with gym-MiniGrid • Aug 6, 2020
Using Convolutional Neural Networks in PyTorch • Jul 29, 2020
Convolutional Neural Networks in PyTorch • Jul 29, 2020
Artificial Neural Networks in PyTorch • Jul 28, 2020
Introduction to PyTorch • Jul 28, 2020
Reinforcement_Learning
REINFORCE on CartPole-v0 • May 12, 2021
Cross-Entropy Methods (CEM) on MountainCarContinuous-v0 • May 11, 2021
Deep Q-Network (DQN) on LunarLander-v2 • May 7, 2021
Pixels-to-Control Learning • Mar 6, 2021
Policy Gradient with gym-MiniGrid • Aug 6, 2020
Model-free Policy Iteration with TD Methods • Jun 24, 2020
Model-free Policy Iteration with Monte Carlo Methods • Jun 23, 2020
Model-free Control • Jun 22, 2020
epsilon-Soft Random Action • Jun 22, 2020
Temporal Difference Learning TD(λ) • Jun 17, 2020
Temporal Difference Learning TD(0) • Jun 17, 2020
Monte Carlo Policy Evaluation • Jun 16, 2020
Monte Carlo method - Intro • Jun 15, 2020
Variants of Dynamic Programming • Jun 10, 2020
Value Iteration • Jun 9, 2020
Policy Iteration • Jun 9, 2020
Finding Optimal Policy • Jun 8, 2020
Policy Evaluation • Jun 6, 2020
Dynamic Programming for solving Bellman equation • Jun 5, 2020
Bellman equations and Markov decision process • Jun 5, 2020
Scikit-Image
Introducing Image Processing and scikit-image • Jul 31, 2020
Software Engineering
Software Engineering Practices, Part 2 • May 25, 2020
Software Engineering Practices, Part 1 • May 21, 2020
Statistics
Counting • Sep 9, 2020
Sets • Sep 2, 2020
Introduction to Probability and Statistics • Aug 30, 2020
Correlation and Experimental Design • Aug 28, 2020
More Distributions and the Central Limit Theorem • Aug 28, 2020
Random Numbers and Probability • Aug 26, 2020
Summary Statistics with Python • Aug 26, 2020
Disney Movies and Box Office Success • Aug 23, 2020
Earthquakes and oil mining in Oklahoma • Jun 24, 2020
Statistical seismology and the Parkfield region • Jun 24, 2020
The Current Controversy of the 2013 World Championships • Jun 24, 2020
Analysis of results of the 2015 FINA World Swimming Championships • Jun 23, 2020
Fish sleep and bacteria growth - A review of Statistical Thinking I and II • Jun 23, 2020
Advanced Applications of Simulation • Jun 22, 2020
Resampling methods • Jun 22, 2020
Probability and data generation process • Jun 21, 2020
Basics of randomness and simulation • Jun 21, 2020
Estimating Model Parameters • Jun 21, 2020
Making Model Predictions • Jun 20, 2020
Building Linear Models • Jun 19, 2020
Exploring Linear Trends • Jun 19, 2020
Statistical Fallacies • Jun 1, 2020
Putting it all together - a case study • May 28, 2020
Introduction to hypothesis testing • May 28, 2020
Bootstrap confidence intervals • May 27, 2020
Parameter estimation by optimization • May 27, 2020
Thinking probabilistically - Continuous variables • May 26, 2020
Thinking probabilistically - Discrete variables • May 26, 2020
Quantitative exploratory data analysis • May 26, 2020
Graphical exploratory data analysis • May 26, 2020
Tensorflow
Custom Layers in Tensorflow 2 • Feb 8, 2022
Custom Loss Function in Tensorflow 2. • Feb 8, 2022
Practice with the Tensorflow 2 Functional API. • Feb 5, 2022
Pixels-to-Control Learning • Mar 6, 2021
Debiasing Facial Detection Systems • Feb 27, 2021
Music Generation • Feb 14, 2021
Application and Tips for Machine Learning • Sep 11, 2020
Softmax Regression • Sep 10, 2020
Logistic Regression/Classification • Sep 9, 2020
Multi-variable Linear Regression • Sep 8, 2020
Cost Minimization using Gradient Descent • Sep 7, 2020
Simple Linear Regression with Tensorflow • Sep 5, 2020
Tensorflow-Keras
The Power of Image Augmentation • Jul 30, 2021
RNN - Many-to-many bidirectional • Dec 10, 2020
RNN - Many-to-many • Dec 9, 2020
RNN - Many-to-one stacking • Dec 8, 2020
RNN - Many-to-one • Dec 6, 2020
RNN Basic • Oct 26, 2020
Image Classification with Cat and Dog • Oct 16, 2020
Super-Resolution Convolutional Neural Network • Oct 13, 2020
CNN with MNIST dataset • Oct 10, 2020
CNN Basic • Oct 7, 2020
Training Hello world model for Microcontrollers • Sep 24, 2020
Image Classification with Fashion MNIST • Sep 21, 2020
Several Tips for Improving Neural Network • Sep 18, 2020
Understanding and Improving Deep Convolutional Networks in Keras • Aug 4, 2020
Going Deeper Convolutions in Keras • Aug 4, 2020
Using Convolutions in Keras • Aug 3, 2020
Image Processing With Neural Networks • Aug 3, 2020
Multiple Outputs in Keras • Jul 28, 2020
Multiple Inputs in Keras • Jul 28, 2020
Two Input Networks Using Categorical Embeddings, Shared Layers, and Merge Layers • Jul 27, 2020
The Keras Functional API • Jul 27, 2020
Advanced Model Architectures • Jul 26, 2020
Improving Your Model Performance • Jul 23, 2020
Going Deeper • Jul 23, 2020
Introducing Keras • Jul 22, 2020
Fine-tuning keras models • Jul 21, 2020
Building deep learning models with keras • Jul 21, 2020
High Level APIs • Jul 20, 2020
Neural Networks • Jul 20, 2020
Linear models • Jul 19, 2020
Introduction to TensorFlow • Jul 18, 2020
Tensorflow-Lite
Training Hello world model for Microcontrollers • Sep 24, 2020
Tensorflow_probability
VAE for the CelebA dataset • Sep 14, 2021
KL Divergence Layers • Sep 14, 2021
Maximizing the ELBO • Sep 14, 2021
Minimizing Kullback-Leibler Divergence • Sep 13, 2021
Encoders and decoders • Sep 13, 2021
RealNVP for the LSUN bedroom dataset • Sep 8, 2021
AutoRegressive flows and RealNVP • Sep 8, 2021
Subclassing Bijectors • Sep 7, 2021
The TransformedDistribution class • Sep 7, 2021
Bijectors • Aug 30, 2021
Bayesian Convolutional Neural Network • Aug 26, 2021
Reparameterization layers • Aug 24, 2021
DenseVariational Layers • Aug 24, 2021
Probabilistic Layers • Aug 23, 2021
The DistributionLambda Layer • Aug 19, 2021
Maximum Likelihood Estimation - how neural networks learn • Aug 19, 2021
Trainable Distributions • Aug 18, 2021
Naive Bayes and logistic regression • Aug 18, 2021
Sampling and log probs • Aug 13, 2021
Broadcasting Rules in Tensorflow Probability • Aug 13, 2021
Independent Distribution • Aug 12, 2021
Univariate Distribution • Aug 11, 2021
Multivariate Distribution • Aug 11, 2021
Time_Series_Analysis
Analyze Your Runkeeper Fitness Data • Aug 22, 2020
Validating and Inspecting Time Series Models • Jun 18, 2020
Predicting Time Series Data • Jun 18, 2020
Time Series as Inputs to a Model • Jun 17, 2020
Time Series and Machine Learning Primer • Jun 17, 2020
Seasonal ARIMA Models • Jun 16, 2020
The Best of the Best Models • Jun 16, 2020
Fitting the Future with time series analysis • Jun 15, 2020
ARMA Models • Jun 15, 2020
Case Study in time series analysis • Jun 14, 2020
Work with Multiple Time Series • Jun 13, 2020
Seasonality, Trend and Noise • Jun 13, 2020
Summary Statistics and Diagnostics • Jun 12, 2020
Introduction of visualization in time series analysis • Jun 12, 2020
Putting it all together - Building a value-weighted index • Jun 12, 2020
Window Functions - Rolling and Expanding Metrics • Jun 11, 2020
Basic Time Series Metrics & Resampling • Jun 10, 2020
Working with Time Series in Pandas • Jun 9, 2020
Putting It All Together • Jun 9, 2020
Moving Average (MA) and ARMA Models • Jun 8, 2020
Autoregressive (AR) Models • Jun 8, 2020
Some Simple Time Series • Jun 7, 2020
Correlation and Autocorrelation • Jun 7, 2020
Udacity
REINFORCE on CartPole-v0 • May 12, 2021
Cross-Entropy Methods (CEM) on MountainCarContinuous-v0 • May 11, 2021
Deep Q-Network (DQN) on LunarLander-v2 • May 7, 2021
Software Engineering Practices, Part 2 • May 25, 2020
Software Engineering Practices, Part 1 • May 21, 2020
Vision
K-Means Clustering for Imagery Analysis • Oct 26, 2020
Image Classification with Cat and Dog • Oct 16, 2020
Super-Resolution Convolutional Neural Network • Oct 13, 2020
Masks and Filters in Biomedical Image Analysis • Aug 15, 2020
Naive Bees Image Loading and Processing • Aug 14, 2020
Exploration in Biomedical Image Analysis • Aug 13, 2020
Object Recognition with ALL-CNN • Aug 11, 2020
Understanding and Improving Deep Convolutional Networks in Keras • Aug 4, 2020
Going Deeper Convolutions in Keras • Aug 4, 2020
Using Convolutions in Keras • Aug 3, 2020
Image Processing With Neural Networks • Aug 3, 2020
Advanced Operations, Detecting Faces and Features • Aug 2, 2020
Image restoration, Noise, Segmentation and Contours • Aug 2, 2020
Filters, Contrast, Transformation and Morphology • Aug 2, 2020
Introducing Image Processing and scikit-image • Jul 31, 2020
Visualization
Matplotlib Tutorial • Sep 9, 2020
Up and Down With the Kardashians • Aug 20, 2020
Comparing Cosmetics by Ingredients • Aug 19, 2020
Exploring the Bitcoin Cryptocurrency Market • Aug 13, 2020
Creating a choropleth building permit density in Nashville • Jul 3, 2020
GeoSeries and folium • Jul 2, 2020
Creating and joining GeoDataFrames • Jul 1, 2020
Building 2-layer maps - combining polygons and scatterplots • Jul 1, 2020
Layouts, Interactions, and Annotations • Jun 30, 2020
Basic plotting with Bokeh • Jun 30, 2020
Visualization in the data science workflow • Jun 30, 2020
Showing uncertainty • Jun 29, 2020
Using color in your visualizations • Jun 28, 2020
Customizing Seaborn Plots • Jun 27, 2020
Visualizing a Categorical and a Quantitative Variable • Jun 26, 2020
Visualizing Two Quantitative Variables • Jun 26, 2020
Introduction to Seaborn • Jun 26, 2020
Highlighting your data • Jun 26, 2020
Sharing visualizations with others • Jun 26, 2020
Quantitative comparisons and statistical visualizations • Jun 26, 2020
Plotting time-series • Jun 26, 2020
Introduction to Matplotlib • Jun 26, 2020
Case Study in time series analysis • Jun 14, 2020
Work with Multiple Time Series • Jun 13, 2020
Seasonality, Trend and Noise • Jun 13, 2020
Summary Statistics and Diagnostics • Jun 12, 2020
Introduction of visualization in time series analysis • Jun 12, 2020
Visualization with hierarchical clustering and t-SNE • Jun 1, 2020
Visual exploratory data analysis • May 25, 2020