Rohail's starred repositories
Deep-Reinforcement-Learning-Hands-On
Hands-on Deep Reinforcement Learning, published by Packt
Advanced-Deep-Learning-with-Keras
Advanced Deep Learning with Keras, published by Packt
Robyn
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
Doing_bayesian_data_analysis
Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke
Statistical-Rethinking-with-Python-and-PyMC3
Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
Generative-Adversarial-Networks-Projects
Generative Adversarial Networks Projects, published by Packt
Python-Natural-Language-Processing-Cookbook
Python Natural Language Processing Cookbook, published by Packt
Python-Reinforcement-Learning-Projects
Python Reinforcement Learning Projects, published by Packt
pymc3_vs_pystan
Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg
vanilla-machine-learning
vanilla machine learning
Building-Recommendation-Systems-with-Python
Building Recommendation Systems with Python [Video], by Packt Publishing
ploomber-engine
A toolbox 🧰 for Jupyter notebooks 📙: testing, experiment tracking, debugging, profiling, and more!
Learning-Generative-Adversarial-Networks
Learning-Generative-Adversarial-Networks, published by Packt
coverage-threshold
A command line tool for checking coverage reports against configurable coverage minimums.
Bayesian_Smoothing_EyeMovement
Repository of my talk for Bayes@Lund 2017
pymc3_examples
Updated repo for self-contained pymc3 examples
-Real-World-Python-Deep-Learning-Projects-v-
Real-World Python Deep Learning Projects [Video] by Packt Publishing
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Ipython Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Machine-Learning-Experimentation-with-TensorBoard
Machine Learning Experimentation with TensorBoard
awesome-bayes
List of resources for bayesian inference
Deep-Learning-with-Keras-V-
Deep Learning with Keras(V) by Packt Publishing
bayesian-stats-modelling-tutorial
How to do Bayesian statistical modelling using numpy and PyMC3
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.