# curiousily/Deep-Learning-For-Hackers

<https://repo.masters-masters.com/repos/curiousily/Deep-Learning-For-Hackers>

[Accueil](https://repo.masters-masters.com/) › [curiousily](https://repo.masters-masters.com/owners/curiousily) › [Deep-Learning-For-Hackers](https://repo.masters-masters.com/repos/curiousily/Deep-Learning-For-Hackers)

curiousily/Deep-Learning-For-Hackers, dépôt open source à 1 079 étoiles sur GitHub. Carte Bêta de RepoMasters. Machine Learning tutorials with TensorFlow 2…

| Champ | Valeur |
| --- | --- |
| Propriétaire | [curiousily](https://repo.masters-masters.com/owners/curiousily) |
| Étoiles | 1 079 |
| Forks | 430 |
| Langage | [Jupyter Notebook](https://repo.masters-masters.com/languages/jupyter-notebook) |
| Licence | MIT |
| Création | 2019 |
| Sujets | deep-learning, tensorflow, machine-learning, artificial-intelligence, python, keras, neural-networks, jupyter-notebooks, tensorflow-tutorial, lstms |
| Rang | [Bêta (700 à 1 999 ★)](https://repo.masters-masters.com/ranks/box_office) |
| Voir sur GitHub | [curiousily/Deep-Learning-For-Hackers](https://github.com/curiousily/Deep-Learning-For-Hackers) |

## Fiche du dépôt

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Rang des dépôts qui ont 700 à 1 999 ★ sur GitHub. Probabilité publiée par carte tirée : 6 %. Rareté : Rare.

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