DataCamp Project Solutions
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Updated
Aug 7, 2024 - Jupyter Notebook
DataCamp Project Solutions
Bootcamp to learn basics in Machine Learning
♂️♀️ Detect a person's gender from a voice file (90.7% +/- 1.3% accuracy).
Latest Data Science Materials
This repository contains study materials in the form of presentations (and Python codes) to various Machine Learning techniques and also contains some sample data to practice these algorithms
模仿 TensorFlow 写的极简深度学习框架,仅供练习目的
Machine Learning Workshop
Exercises | Machine Learning Crash Course | Google Developers
Welcome to the Machine Learning Roadmap! This comprehensive guide will take you from the basics to becoming proficient in machine learning. Whether you're a beginner or looking to expand your skills, this roadmap will provide you with a structured path to follow.
coding along with ML course from eduonix, doing real projects
ML Algorithm implementation from scratch for practice
Machine learning algorithm solves multi-class classification problem of video games content rating (without playing it). Quantitative Methods for Computer Science exam project.
Implementation of machine learning algorithms from scratch using python.
Machine Learning project built to practice and improve coding and deployment skills using python, scikit-learn, jupyter-notebooks, and some visualization packages.
Machine Learning studies. Current approaches: Data processing, model training, evaluation performance and parameter adjustment for better performance.
Machine Learning A-Z™ Hands-On Python & R In Data Science
The repository contains exercises on Machine Learning algorithms in R, using RStudio. Used to dive into ML, data preprocessing, data visualisation, and data exploration.
An intelligent traffic management system to guide traffic authorities understand the trends of traffic and predict the future traffic conditions so that they can prepare themselves. Along with this it gives many other features to improve traffic control.
PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM
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