Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
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Updated
Oct 19, 2024 - HTML
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
(CGCSTCD'2017) An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations. CGCSTCD = China Graduate Contest on Smart-city Technology and Creative Design
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!
Curso de Introducción a Machine Learning con Python
Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web
Use unsupervised and supervised learning to predict stocks
Top 200 deep learning Github repositories sorted by the number of stars.
deeplearning.ai , By Andrew Ng, All video link
A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
simple neural network library in ANSI C
Top 100 trending deep learning repositories sorted by the number of stars gained on a specific day.
Udemy Derin Öğrenmeye Giriş Kursunun Uygulamaları ve Daha Fazlası
Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database
NiuTensor is an open-source toolkit developed by a joint team from NLP Lab. at Northeastern University and the NiuTrans Team. It provides tensor utilities to create and train neural networks.
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This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms
My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings 👍
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