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PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
A complete computer science study plan to become a software engineer.
This repository contains mini projects in machine learning with notebook files
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
This is the code for the "How to Do Linear Regression the Right Way" live session by Siraj Raval on Youtube
This is a collection of iPython notebooks from my course on data mining. Data used in the notebooks can be downloaded from the given links in the notebooks.
A game theoretic approach to explain the output of any machine learning model.
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
This is the code for "Logistic Regression" By Siraj Raval on Youtube
A collection of Bayesian data analysis recipes using PyMC3
Python Deep Dive Course - Accompanying Materials
Building Decision Trees From Scratch In Python
2nd Place Solution 💰🥈
Youtube tutorial associated content
A compiled list of kaggle competitions and their winning solutions for classification problems.
Predicting if a patient is suffering from Diabetes or not using Machine Learning in Python. Give the repo a star if you found it informative.
Anomaly detection tutorial on univariate time series with an auto-encoder
This is a very in depth explination of naive bayes w.r.t implementation in python which can be used in Machine Learning applications.
A collection of scripts and examples created while answering questions from the greater Dash community
Linear Regression from scratch
Pandas tutorial for SciPy 2019
A compiled list of kaggle competitions and their winning solutions for regression problems.
Applying machine learning to predict loan charge-offs on LendingClub.com
For the pandas tutorial at PyData Seattle: https://www.youtube.com/watch?v=otCriSKVV_8
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
Modin: Scale your Pandas workflows by changing a single line of code
Materials for PyCon 2017 presentation on optimizing Pandas code