Deep-Learning-Specialization-Coursera and Machine-Learning-AndrewNg-DeepLearning.AI

Deep-Learning-Specialization-Coursera
51
Established
Machine-Learning-AndrewNg-DeepLearning.AI
51
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 462
Forks: 380
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 352
Forks: 186
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Deep-Learning-Specialization-Coursera

abdur75648/Deep-Learning-Specialization-Coursera

This repo contains the updated version of all the assignments/labs (done by me) of Deep Learning Specialization on Coursera by Andrew Ng. It includes building various deep learning models from scratch and implementing them for object detection, facial recognition, autonomous driving, neural machine translation, trigger word detection, etc.

This collection of assignments provides practical examples for understanding and building advanced artificial intelligence models. It offers ready-to-use code for tasks like recognizing objects in images, identifying faces, and translating languages. Anyone learning or teaching deep learning concepts would find these practical solutions helpful.

deep-learning-education computer-vision natural-language-processing machine-learning-training

About Machine-Learning-AndrewNg-DeepLearning.AI

azminewasi/Machine-Learning-AndrewNg-DeepLearning.AI

Contains all course modules, exercises and notes of ML Specialization by Andrew Ng, Stanford Un. and DeepLearning.ai in Coursera

This specialization helps aspiring AI practitioners master fundamental machine learning concepts and build practical skills. It takes learners from basic data and problems to functional models for prediction, classification, and recommendation. It's designed for anyone looking to start a career in machine learning or apply AI techniques to real-world problems.

AI-education data-science-training predictive-modeling recommendation-systems career-transition

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