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100 Days Of Ml Code ⭐ 42,417

100 Days of ML Coding

Python Machine Learning Book ⭐ 11,645

The "Python Machine Learning (1st edition)" book code repository and info resource

General Assembly's 2015 Data Science course in Washington, DC

Fast Best-Subset Selection Library

Ds_and_ml_projects ⭐ 110

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

A repository for recording the machine learning code

Skorecard ⭐ 71

scikit-learn compatible tools for building credit risk acceptance models

Nba Predict ⭐ 46

Predicts Daily NBA Games Using a Logistic Regression Model

The Deep Learning With Keras Workshop ⭐ 40

An Interactive Approach to Understanding Deep Learning with Keras

Icc 2019 Wc Prediction ⭐ 39

Predicting the winner of 2019 cricket world cup using random forest algorithm

Augmented Interpretable Models ⭐ 35

Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.

Text Classification Cn ⭐ 33

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

Wisconsin Breast Cancer ⭐ 27

[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

Breast Cancer Scikitlearn ⭐ 27

simple tutorial on Machine Learning with Scikitlearn

Trajectory Analysis And Classification In Python Pandas And Scikit Learn ⭐ 25

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently trajectories.

Tariq Ml Models ⭐ 14

This repository contains all my implemented Machine Learning and Deep Learning projects. All my learning from different books and the internet is reflected here. The models are trained on a variety of problems including NLP, CV and other domains. The main focus of this repository is to showcase my learning journey and the projects I have worked on.

Predicting Baseball Statistics ⭐ 14

Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn

Ibm Final Project Machine Learning ⭐ 14

Final project of IBM's course https://www.coursera.org/learn/machine-learning-wi on coursera

Machine Learning Course ⭐ 13

Machine Learning Course @ Santa Clara University

Forecasting Weather Using Machine Learning ⭐ 11

Forcasting Weather Using Multinomial Logistic Regression, Decision Tree, Naïve Bayes Multinomial, and Support Vector Machine

Application that predicts the number of stars that of a Yelp Review in realtime as a reviewer types it. Runs as a microservice-based application using Node.js, Python, and Docker. Displays results from Google Natural Language API and a custom trained classification models.

Sklearn Wrapper ⭐ 9

A web.py service for interacting with scikit-learn

Machinelearning_exercises_python_scikit Learn ⭐ 8

Python＆機械学習ライブラリ scikit-learn の使い方の練習コード集。機械学習の理論解説付き

Machine Learning ⭐ 7

Fundamentals & projects

Data Science ⭐ 7

EDA and Machine Learning Models in R and Python (Regression, Classification, Clustering, SVM, Decision Tree, Random Forest, Time-Series Analysis, Recommender System, XGBoost)

Healthytrees ⭐ 6

🌿🗽Analysis of health of NYC trees with GIS, logistic regression & random forest 🏙 🌳 National Day of Civic Hacking 2016

Clarusway_machine_learning_course ⭐ 6

This repository contains the Machine Learning lessons I took from the Clarusway Bootcamp between 10 Aug - 14 Sep 2022 and includes 17 sessions, 5 labs, 4 case studies, 5 weekly agendas, and 3 projects.

Enron_fraud ⭐ 6

Build a model to predict employees involved in Enron fraud case based on email & financial data set. Use feature selection & engineering, algorithm selection, & model selection based on F1 score, precision, & recall.

Anomaly Detection ⭐ 5

Easy to understand classification problem from a highly skewed kaggle dataset. Solved using logistic regression and SVM, code inspired from top contributor.

Machine Learning Python Bootcamp ⭐ 5

Basic exercises on Machine Learning with Python , Reference Book : Python for Probability, Statistics, and Machine Learning by José Unpingco

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