Pooret's Stars
labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
TemesgenGT/Transfer-Learning-for-Pneumonia-Detection
haberkornm/Convolutional-Neural-Network-Of-Corn-Leaf-Disease-Images
Project developing a CNN for the classification of corn and maize leaf disease images. Image dataset is composed of healthy, gray leaf spot, common rust, and blight leaf images.
Bench-amblee/yelp_sentiment_analysis
Natural Language Processing Project
MIT-LCP/mimic-iv
Deprecated. For the latest MIMIC-IV code, please refer to: https://github.com/MIT-LCP/mimic-code
bayesian-optimization/BayesianOptimization
A Python implementation of global optimization with gaussian processes.
afshinea/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
patonlab/CASCADE
CAlculation of NMR Chemical Shifts using Deep LEarning
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
mdipietro09/DataScience_ArtificialIntelligence_Utils
Examples of Data Science projects and Artificial Intelligence use-cases
RishabhKr97/StockIt
Predicting bullish or bearish sentiment of stocks (Apple, Google, Amazon) using analysis of Stocktwits tweets.
ProsusAI/finBERT
Financial Sentiment Analysis with BERT
explosion/spacy-course
👩🏫 Advanced NLP with spaCy: A free online course
sdesaidata/Springboard
Springboard Projects
springboard-curriculum/featuretools
Adapted exercise from here: https://github.com/Featuretools/predict-customer-churn/blob/master/churn/3.%20Feature%20Engineering.ipynb
foxbook/atap
Code for Applied Text Analysis with Python
mml-book/mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
NathanEpstein/pydata-london
anubhavanand12qw/STOCK-PRICE-PREDICTION-USING-TWITTER-SENTIMENT-ANALYSIS
The coding has been done on Python 3.65 using Jupyter Notebook. This program fetches LIVE data from TWITTER using Tweepy. Then we clean our data or tweets ( like removing special characters ). After that we perform sentiment analysis on the twitter data and plot it for better visualization. The we fetch the STOCK PRICE from yahoo.finance and add it to the data-set to perform prediction. We apply many machine learning algorithms like (random forest, MLPClassifier, logistic regression) and train our data-set. Then we perform prediction on untrained data and plot it with the real data and see the accuracy.
wbrenna/inventory
Use a barcode reader to scan the foods in your house and add them to a database. See legacy for zbarcam integration. Master integrates with a USB barcode laser scanner.
practical-tutorials/project-based-learning
Curated list of project-based tutorials
TracyRenee61/Traffic-Forecasting
McKinsey Analytics competition
sw385/Meal-Plan-Generator
Given macronutrient goals and a list of foods, return a combination of foods to reach those goals.
rasbt/python-machine-learning-book
The "Python Machine Learning (1st edition)" book code repository and info resource
springboard-curriculum/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks