mango VS coursera-deep-learning-specialization

Compare mango vs coursera-deep-learning-specialization and see what are their differences.

mango

Parallel Hyperparameter Tuning in Python (by ARM-software)
hyperparameter-optimization blackbox-optimization hyperparameter-tuning parallel-computing Machine Learning tuning-parameters sklearn-compatible scipy-compatible tensorflow-examples keras-examples pytorch-compatible bayesian-optimization gaussian-processes kubernetes-deployment cluster-deployment production-system neural-network neural-networks
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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)
Deep Learning Coursera coursera-assignment coursera-specialization coursera-machine-learning andrew-ng andrew-ng-course convolutional-neural-networks cnns recurrent-neural-networks rnns convolutional-neural-network recurrent-neural-network hyperparameter-optimization hyperparameter-tuning neural-network neural-networks neural-machine-translation neural-style-transfer regularization
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mango coursera-deep-learning-specialization
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311 2,703
1.3% -
5.8 6.4
2 months ago 25 days ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 -
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mango

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coursera-deep-learning-specialization

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What are some alternatives?

When comparing mango and coursera-deep-learning-specialization you can also consider the following projects:

Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

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

machine_learning_basics - Plain python implementations of basic machine learning algorithms

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]

vizier - Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

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

neural-tangents - Fast and Easy Infinite Neural Networks in Python

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

Bayesian-Optimization-in-FSharp - Bayesian Optimization via Gaussian Processes in F#

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!

Spotify_Song_Recommender - This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.

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

mango vs Hyperactive coursera-deep-learning-specialization vs cs231n mango vs machine_learning_basics coursera-deep-learning-specialization vs stanford-CS229 mango vs vizier coursera-deep-learning-specialization vs deeplearning-notes mango vs neural-tangents coursera-deep-learning-specialization vs Emotion_Detection_CNN_keras mango vs Bayesian-Optimization-in-FSharp coursera-deep-learning-specialization vs start-machine-learning mango vs Spotify_Song_Recommender coursera-deep-learning-specialization vs stanford-cs229