Probability and Statistics for Data Science: A self-contained introduction to probability and statistics for data science, including a free pdf, 103 Python notebooks using 23 real-world datasets, 1…

Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022

Data Science Using Python

A Free Newsletter for Quantitative and Algorithmic Trading, Portfolio Analysis, and Investing

Master programming by recreating your favorite technologies from scratch.

📺 Discover the latest machine learning / AI courses on YouTube.

🔥Highlighting the top ML papers every week.

List of Computer Science courses with video lectures.

An awesome Analytics Engineering repository to learn and apply for real world problems.

Oxford Deep NLP 2017 course

Pairs trading strategy that includes a research pipeline for identifying and selecting pairs. Tests all possible pairs in a universe for cointegration using the Johansen test, then runs in-sample b…

The Data Engineering Cookbook

A fast, extensible, transparent python library for backtesting quantitative strategies.

llama3 implementation one matrix multiplication at a time

Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.

📝 An awesome Data Science repository to learn and apply for real world problems.

Jupyter notebook tutorials for football analytics

Data Science Feature Engineering and Selection Tutorials

This repository contains everything you need to become proficient in Data Engineering

Resources for the PyCon 2017 tutorial, "Exploratory data analysis in python"

The repo with the queries I wrote for Luke Barousse's SQL course.

Contains code and dataset for "The Researchers' Guide" YouTube channel

Streamlit Data Science and ML Apps in Python

Collection of data science projects in Python

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

For extensive instructor led learning

📝 An awesome Data Science repository to learn and apply for real world problems.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…