Wael Muzarzaa's repositories
numpy-ml
Machine learning, in numpy
data_science_for_all
Code and resources for my blog and articles to share Data Science and AI knowledge and learnings with everyone
appliedml_workshop_dhs_av_2019
Content for Applied ML Workshop @ DataHack Summit 2019
awesome-cheatsheets
👩💻👨💻 Awesome cheatsheets for popular programming languages, frameworks and development tools. They include everything you should know in one single file.
numpy-tutorial
Numpy beginner tutorial
flask-realtime-todo
Realtime CRUD Python application built with Flask, Vanilla JavaScript and Pusher
data-visualization
Misc data visualization projects, examples, and demos: mostly Python (pandas + matplotlib) and JavaScript (leaflet).
Research-Methods-for-Data-Science-with-Python
Research Methods for Data Science with Python
Bible-NLP-and-ML-using-Python
Natural Language Processing and ML Prediction of the Bible
Probability-and-Information-Theory
Probability and Information Theory for Machine Learning
nlp_workshop_iisc19
Hands-on examples showcasing popular NLP applications
Linear-Algebra-Basics
Linear Algebra Fundamentals for Machine Learning
Data-Cleaning-Practical-Examples
Data Cleaning In Python and Julia with Practical Examples
EDA
EDA is an approach to analyzing datasets to summarize their main characteristics often with statistical and visual methods, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task.
python-patterns
A collection of design patterns/idioms in Python
udacity-dend-data-warehousing
Data warehousing Udacity project, for creating a song play ETL pipeline using S3 and Redshift.
Data-Science--Cheat-Sheet
Cheat Sheets
wordcloud2
R interface to wordcloud for data visualization.
Social-Network-Analysis
Social Network Analysis in Python and Julia using Networkx,IGraph and LightGraphs.jl
data_visualization
A collection of my data visualizations, mostly in Python.
feature_engineering_session_dhs18
Contains code and presentation for my interactive hack session, 'Effective Feature Engineering: A Structured Approach to Building Better Machine Learning Models' where we look at two interesting case studies on how to effectively leverage feature engineering and use a structured approach to build good machine learning models. This is created for the purpose of being presented in Analytics Vidhya's DataHack Summit 2018
free-data-science-books
Free resources for learning data science
art_of_data_visualization
The art of effective visualization of multi-dimensional data
NoteBooks-Statistics-and-MachineLearning
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
programming-concepts-for-data-science
Basics of programming: algorithms, data structures, object oriented programming
Data-Warehouse-Concepts-Design-and-Data-Integration
Repo for Data Warehouse Concepts, Design, and Data Integration by University of Colorado System (coursera)(Notes,Assignments, quiz and research papers)
Catch-Tweet-with-Keyword
Get Tweet by giving keyword and do keyword analysis
stanford-statistical-learning
Slides, material and solutions of the popular Statistical Learning course from Stanford's own Hastie & Tibshirani. Join me on my journey to finally try and complete this course after leaving it mid-way atleast 3-4 times due to other commitments!