Collaboration with wangxupeng(https://github.com/wangxupeng)
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- crnn-ctc
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Collaboration with wangxupeng(https://github.com/wangxupeng)
Recommender Learning with Tensorflow2.x
Use supervised learning to illuminate the latent space of GAN for controlled generation and edit
Deep Learning model to analyze a large corpus of clear text passwords.
A modern, web-based photo management server. Run it on your home server and it will let you find the right photo from your collection on any device. Smart filtering is made possible by object recognition, face recognition, location awareness, color analysis and other ML algorithms.
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE
Named Entity Recognition (LSTM + CRF) - Tensorflow
TinyML AI inference library
Gaussian processes in TensorFlow
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
Generic U-Net Tensorflow implementation for image segmentation
:unlock: Lip Reading - Cross Audio-Visual Recognition using 3D Architectures
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
TensorFlow template application for deep learning
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
Provide an input CSV and a target field to predict, generate a model + code to run it.
A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!
1st place solution
Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.
The deeplearning algorithms implemented by tensorflow
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model
StyleGAN2 with adaptive discriminator augmentation (ADA) - Official TensorFlow implementation
Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier