fchollet /
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
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ShrinivasanT / repository
Deep Learning with CIFAR-10: A hands-on project exploring image classification using Convolutional Neural Networks (CNNs). This repository contains a Jupyter Notebook implementing model training, evaluation, and visualization on the CIFAR-10 dataset.
This repository contains a Jupyter Notebook that demonstrates image classification on the CIFAR-10 dataset using Deep Learning (Convolutional Neural Networks).
The project covers data preprocessing, model building, training, evaluation, and visualization of results.
You can read more about CIFAR-10 here.
Install dependencies with:
pip install tensorflow keras matplotlib numpy
Selected from shared topics, language and repository description—not editorial ratings.
fchollet /
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
curiousily /
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
dipanjanS /
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
erhwenkuo /
Jupyter notebooks for using & learning Keras
DeqianBai /
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
curiousily /
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)