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All the slides, accompanying code and exercises all stored in this repo. 🎈

A day to day plan for this challenge. Covers both theoritical and practical aspects

Create HTML profiling reports from pandas DataFrame objects

Association Rule Mining from Spatial Data for Crime Analysis

Code, Notebooks and Examples from Practical Business Python

A collection of notebooks of my Machine Learning class written in python 3

Virgilio is developed and maintained by these awesome people. You can email us virgilio.datascience (at) gmail.com or join the Discord chat.

General Assembly's 2015 Data Science course in Washington, DC

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

brief introduction to Python for machine learning

Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.

Alpine Container for Machine Learning

For extensive instructor led learning

Exercises for hierarchical clustering with Python 3 and scipy as Jupyter Notebooks

I will update this repository to learn Machine learning with python with statistics content and materials

Disease Prediction based on Symptoms.

50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster

Credit Risk analysis by using Python and ML

Tutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal

This repository is my attempt to help Data Science aspirants gain necessary Data Visualization skills required to progress in their career. It includes all the types of plot offered by Seaborn, applied on random datasets.

Dive into Machine Learning with Python Jupyter notebook and scikit-learn! First posted in 2016, maintained as of 2021. Pull requests welcome.

🤖⚡️ scikit-learn tips

IPython widgets, interactive plots, interactive machine learning

Achieve your marketing goals with the data analytics power of Python

This repository contains notes and projects of Data scientist track from dataquest course work.

🎓 Jupyter notebooks from UFC data science course

🐍 Learn Python and Pandas from the ground up

A guide to getting started with Data Science and ML.

The blog post about Kubeflow, including all materials

GitHub Action for repo2docker

HandySpark - bringing pandas-like capabilities to Spark dataframes

This repository provides everything you need to get started with Python for (social science) research.

R on Apache Spark (SparkR) tutorials for Big Data analysis and Machine Learning as IPython / Jupyter notebooks

There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.

Jupyter notebook and datasets from the pandas Q&A video series

Introduction to pandas Treehouse course

This is Andrew NG Coursera Handwritten Notes.

Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/

👨🏽‍🏫You can learn about what data science is and why it's important in today's modern world. Are you interested in data science?🔋

Visualizer for pandas data structures

Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)

📚 Various cheatsheets in PDF

🛠 All-in-one web-based IDE specialized for machine learning and data science.

Functionalities in Excel translated to Python

The "Python Machine Learning (1st edition)" book code repository and info resource

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Data Science Hacks consists of tips, tricks to help you become a better data scientist. Data science hacks are for all - beginner to advanced. Data science hacks consist of python, jupyter notebook, pandas hacks and so on.

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications

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A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

The "Python Machine Learning (2nd edition)" book code repository and info resource

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).