94 results for “topic:machine-learning-practice”
DataCamp Project Solutions
Bootcamp to learn the basics for 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
A carefully curated collection of machine learning notes, resources, projects, and datasets designed to guide you through the ML landscape effectively.
模仿 TensorFlow 写的极简深度学习框架,仅供练习目的
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.
Machine Learning Workshop
Exercises | Machine Learning Crash Course | Google Developers
coding along with ML course from eduonix, doing real projects
统计学习方法-python练习
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 algorithm solves multi-class classification problem of video games content rating (without playing it). Quantitative Methods for Computer Science exam project.
ML Algorithm implementation from scratch for practice
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.
A hands-on approach to learning machine learning, with practical examples to grasp essential concepts.
The repository contains exercises on Machine Learning algorithms in R, using RStudio. Used to dive into ML, data preprocessing, data visualisation, and data exploration.
Machine Learning A-Z™ Hands-On Python & R In Data Science
Machine Learning studies. Current approaches: Data processing, model training, evaluation performance and parameter adjustment for better performance.
ELEC 8900: Machine Learning [ML] | Semester III | MEng Computer Engineering
Implementations of Machine Learning algorithms with Python and Numpy.
PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM
This repository gives beginners and newcomers in the field of AI and ML a chance to understand the inner workings of popular learning algorithms by presenting them with a simple way to analyze the implementation of ML and DL algorithms in pure python using only numpy as a backend for linear algebraic computations.
🧠🤖 Want to learn how to build neural networks from scratch? Follow along and create your own machine learning library.
This repository contains some machine learning projects as a practise on machine learning course on Coursera for Prof. Andrew Ng from Stanford University.
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k-NN Iris Dataset Classification - Using scikit-learn
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