This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

Collection of Artificial Intelligence projects.

Best Practices on Recommendation Systems

Teaching Materials for Dr. Waleed A. Yousef

Applying Data Science and Machine Learning to Solve Real World Business Problems

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

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

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

Tutorial: Web scraping in Python with Beautiful Soup

Tutorial Sessions for SciPy Con 2019

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

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

RadIO is a library for data science research of computed tomography imaging

A Chinese translation of Jake Vanderplas' "Python Data Science Handbook". 《Python数据科学手册》在线Jupyter notebook中文翻译

Content-Based Recommender System recommends movies similar to the movie user likes and analyses the sentiments on the reviews given by the user for that movie.

Datasets, tools, and benchmarks for representation learning of code.

Amacımız Türkçe NLP literatüründeki birçok farklı sorunu bir arada çözebilen, eşsiz yaklaşımlar öne süren ve literatürdeki çalışmaların eksiklerini gideren open source bir yazım destekleyicisi/denetleyicisi oluşturmak. Kullanıcıların yazdıkları metinlerdeki yazım yanlışlarını derin öğrenme yaklaşımıyla çözüp aynı zamanda metinlerde anlamsal analizi de gerçekleştirerek bu bağlamda ortaya çıkan yanlışları da fark edip düzeltebilmek.

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

🟣 Object detection of abstract shapes with neural networks

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