TensorFlow: Normalizing Flow Models
Generative models are a kind of statistical model that aims to learn the underlying data distribution itself. If a generative...
TensorFlow: Probabilistic Deep Learning Models
Unfortunately, deep learning models aren’t always accurate, especially when asked to make predictions on new data points that are dissimilar to the...
Distribution Objects in TensorFlow Probability
We’ll be making extensive use of the TensorFlow Probability library to help us develop probabilistic deep learning models. The...
My #99 course certificate from Coursera
Customising Your Models with TensorFlow 2Imperial College London I highly recommend this course to everyone who is willing...
Customizing Models, Layers and Training Loops
Subclassing Models The model subclassing and custom layers give you even more control over how the model is...
Sequential Data and Recurrent Neural Networks
Sequential data is data that has a natural sequential structure built into it, like text data or audio...
Keras and Tensorflow Datasets
Data pipelines are for loading, transforming, and filtering a wide range of different data for use in your...
The Keras Functional API
The reason you might want to use the Functional API (instead of the Sequential API) is if you...
My #77 course certificate from Coursera
Understanding and Visualizing Data with PythonUniversity of Michigan This is a fantastic statistics course taught in the setting...
Probability, Sampling & Inference
In the 1930s, Jerzy Nayman and others made some very important breakthroughs in this area and his work...
Visualizing Statistical Data
Statistics: Arts and Sciences Statistics is the subject that encompasses all aspects of learning from data. We are...
My #67 course certificate from Coursera
Getting started with TensorFlow 2Imperial College London Wow this is a wonderful course on Tensorflow! The professor and...
My #61 course certificate (with Honors) from Coursera
Practical Reinforcement LearningHigher School of Economics I am very proud that I survived and completed this thorny but...
Exploration and Planning in Reinforcement Learning
Exploration is needed to find unknown actions which lead to very large rewards. Most of the reinforcement learning...
Reinforcement Learning: Policy Gradient Methods
The problems of value-based methods The idea behind value-based reinforcement learning (say, Q-learning) is to find an optimal...