Tensorflow Developed by the Google Brain Team, TensorFlow is an open-source platform that helps machine learning engineers and data scientists build models and deploy applications easily. With TensorFlow, getting started, building models, and debugging is made easy with access to high-level APIs like Keras. TensorFlow is equipped with features, like state-of-the-art pre-trained models, popular machine learning datasets, and increased ease of execution for mathematical computations, making it popular among seasoned researchers and students alike.
S01: Very basic sample in tensorflow
S02: Define tensor, dynamic and static computation graph
S03: Define learning model optimization in TensorFlow on linear regression
S04: Example of Nural network definition in TensorFlow on fashion mnist dataset
S05: Convolutional neural network in TensorFlow
S06: Recurrent neural network in Tensorflow 2 (sample: LSTM for Text Classification)
S07: DCGAN in Tensorflow 2 on fashion MNist Dataset
S08: Static and dynamic graph model execution time
S09: Using Tensorboard (in example of Nural network definition in TensorFlow on fashion mnist dataset)
S10: Tensorflow Serving