Pinned Repositories
1806
18.06 course at MIT
cookbook-2nd-code
Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]
cs228-material
Teaching materials for the probabilistic graphical models and deep learning classes at Stanford
cs231n.github.io
Public facing notes page
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Deep-Reinforcement-Learning-Hands-On
Hands-on Deep Reinforcement Learning, published by Packt
deepLearningBook-Notes
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
docs
TensorFlow documentation
Ebooks
These are Some useful ebook
examples
Some code examples
pravak114's Repositories
pravak114/ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
pravak114/fastbook
The fastai book, published as Jupyter Notebooks
pravak114/deepLearningBook-Notes
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
pravak114/1806
18.06 course at MIT
pravak114/Supervised-Learning-on-Relational-Databases-with-GNNs
Code to reproduce the results in the paper Supervised Learning on Relational Databases with Graph Neural Networks.
pravak114/pystatsml
Statistics and Machine Learning in Python
pravak114/Deep-Reinforcement-Learning-Hands-On
Hands-on Deep Reinforcement Learning, published by Packt
pravak114/handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
pravak114/Grokking-Deep-Learning
this repository accompanies the book "Grokking Deep Learning"
pravak114/machine-learning-books
a list of machine learning books, covering ML, RL, NLP
pravak114/numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
pravak114/docs
TensorFlow documentation
pravak114/Python-for-Probability-Statistics-and-Machine-Learning-2E
Second edition of Springer Book Python for Probability, Statistics, and Machine Learning
pravak114/pytorch_notebooks
A collection of PyTorch notebooks for learning and practicing deep learning
pravak114/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
pravak114/examples
Some code examples
pravak114/Machine-Learning
pravak114/jupyter
Jupyter metapackage for installation, docs and chat
pravak114/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
pravak114/cs231n.github.io
Public facing notes page
pravak114/LinAlgML
Linear Algebra for Machine Learning Book Exercises
pravak114/your-first-kaggle-submission
How to perform an exploratory data analysis on the Kaggle Titanic dataset and make a submission to the leaderboard.
pravak114/cookbook-2nd-code
Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]
pravak114/scientific-python-lectures
Lectures on scientific computing with python, as IPython notebooks.
pravak114/Ebooks
These are Some useful ebook
pravak114/linear-algebra-for-machine-learning
Basic Linear Algebra for Machine Learning
pravak114/cs228-material
Teaching materials for the probabilistic graphical models and deep learning classes at Stanford
pravak114/python-reference
Python Quick Reference