Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera VS coursera-deep-learning-specialization

Compare Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera vs coursera-deep-learning-specialization and see what are their differences.

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models (by amanchadha)
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Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera coursera-deep-learning-specialization
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Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera

Posts with mentions or reviews of Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera. We have used some of these posts to build our list of alternatives and similar projects.

coursera-deep-learning-specialization

Posts with mentions or reviews of coursera-deep-learning-specialization. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera and coursera-deep-learning-specialization you can also consider the following projects:

Machine-Learning-Specialization-Coursera - Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

cs231n - Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

stanford-CS229 - Python solutions to the problem sets of Stanford's graduate course on Machine Learning, taught by Prof. Andrew Ng [UnavailableForLegalReasons - Repository access blocked]

Basic-Mathematics-for-Machine-Learning - The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

deeplearning-notes - Notes for Deep Learning Specialization Courses led by Andrew Ng.

ML-foundations - Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

Emotion_Detection_CNN_keras - Train and test our algorithm using Convolution Neural Networks and classify emotions in real-time.

Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.

start-machine-learning - A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2024 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

stanford-cs229 - 🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford

Soevnn - A neural net with a terminal-based testing program.