Hussam09's Stars
google-research/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
mnielsen/neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
Sinaptik-AI/pandas-ai
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
diego-vicente/som-tsp
Solving the Traveling Salesman Problem using Self-Organizing Maps
ethen8181/machine-learning
:earth_americas: machine learning tutorials (mainly in Python3)
amaas/stanford_dl_ex
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial
b7leung/MLE-Flashcards
200+ detailed flashcards useful for reviewing topics in machine learning, computer vision, and computer science.
janosh/awesome-normalizing-flows
Awesome resources on normalizing flows.
OpenIntroStat/ims
📚 Introduction to Modern Statistics - A college-level open-source textbook with a modern approach highlighting multivariable relationships and simulation-based inference. For v1, see https://openintro-ims.netlify.app.
ChawlaAvi/Daily-Dose-of-Data-Science
A collection of code snippets from the publication Daily Dose of Data Science on Substack: http://www.dailydoseofds.com/
cvxgrp/cvxbook_additional_exercises
Additional exercises and data for EE364a. No solutions; for public consumption.
rasbt/stat479-deep-learning-ss19
Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison
ShawhinT/YouTube-Blog
Codes to complement YouTube videos and blog posts on Medium.
D-dot-AT/Stock-Prediction-Neural-Network-and-Machine-Learning-Examples
Examples of python neural net and ML stock prediction methods with sample stock data.
je-suis-tm/machine-learning
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression
rstudio-conf-2022/people-analytics-rstats
keithmcnulty/peopleanalytics-regression-book
Handbook of Regression Modeling in People Analytics
akcarsten/Independent_Component_Analysis
From scratch Python implementation of the fast ICA algorithm.
sicarul/xray
xray: The R Package to have X Ray vision on your datasets
Ransaka/GMM-from-scratch
The only guide you need to learn everything about GMM
tlverse/tlverse-handbook
🎯 :closed_book: Targeted Learning in R: A Causal Data Science Handbook
pierrepaleo/ChambollePock
A Python implementation of the Chambolle-Pock algorithm for image processing applications examples
ifenium/My-Solutions-to-The-Python-Workbook-By-Ben-Stephenson-122-of-174-
My Solutions to "The Python Workbook" By Ben-Stephenson
nielsrhansen/CSwR
Computational Statistics with R
PacktPublishing/R-Statistics-Cookbook
R Statistics Cookbook, published by Packt
ctanujit/MATH-370
Data Science and Machine Learning
no37no37/student_result_analysis
Hussam09/faraway
R package, scripts and documentation supporting R books by Julian Faraway
tomMoral/deepinv
PyTorch library for solving imaging inverse problems using deep learning