[Télécharger] ADVANCED DATA SCIENCE NEURAL NETWORK, TENSORFLOW ,KERA PART 1: Advanced Machine Learning, Data Science, AI, Neural Network, Tensorflow, KERA (English Edition) de GICGAC ACADEMY En Ligne

Télécharger ADVANCED DATA SCIENCE NEURAL NETWORK, TENSORFLOW ,KERA PART 1: Advanced Machine Learning, Data Science, AI, Neural Network, Tensorflow, KERA (English Edition) de GICGAC ACADEMY Francais PDF

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Télécharger "ADVANCED DATA SCIENCE NEURAL NETWORK, TENSORFLOW ,KERA PART 1: Advanced Machine Learning, Data Science, AI, Neural Network, Tensorflow, KERA (English Edition)" de GICGAC ACADEMY En Ligne

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The book will provide advanced Machine Learning, Data Science, AI, Neural Network.Details describe with python code1.What is Neural Network?32.What are the various types of Neural network43.What is MLP neural network?54.MLP Model with KERAS105.What is Recurrent Neural network166.When to Use Multilayer Perceptrons?187.When to Use Convolutional Neural Networks?198.When to Use Recurrent Neural Networks?209.What is Backpropagation in Neural Network? Why it is so important?2110.Epochs3011.Batch Size3112.Learning Rate3213.What are the parameters that define a convolutional layer3414.Activation function in Neural Network3515.Binary Step Function – An Activation Function3616.Linear Function – An Activation Function3817.Sigmoid – An Activation Function3918.Tanh – An Activation Function4119.ReLU – An Activation Function4320.Leaky ReLU4521.Softmax – An Activation Function4722.What is the function of optimization in neural networks?4823.What are the types of Optimization Algorithm?4824.What is Gradient descent5025.What are Gradient descent variants5126.SGD - Optimizer5427.RMSprop - Optimizer5628.AdaGrad - Optimizer5829.Adadelta optimizer6130.Adam - Optimizer6231.Adamax – Optimizer6432.Nadam - Optimizer6533.What is Model Parameter?6534.What is Hyperparameter?6635.What is Dropout6636.Using Dropout on Hidden Layers6737.Using Dropout on the Visible Layer6738.Dropout Regularization in Keras6839.Input Dropout to LSTM6940.Recuurent Dropout on LSTM7241.What is Tensorflow?7442.How to install TensorFlow (Linux and Mac OS)7443.How to install TensorFlow (WINDOWS)7444.What is Tensor?7445.How Numpy is different from Tensorflow?7546.How the evaluation on Tensorflow?7547.Write a code in tensorflow for a multiplication with constant value.7648.What is session in tensorflow?7749.How to declare Tensorflow variable7750.How to pass the value to variable?7851.Example how sess.run fetch multiple function values7952.How tensorflow work with numpy values ?8053.What is Placeholders and Feed Dictionaries?8154.What is variable_scope and get_variable of tensorflow?8155.Example Tensorflow – Linear Regression8256.Example Tensorflow – Logistic Regression – mnist data set8757.CNN With Tensorflow9058.Basic example with Session with Tensorflow9459.Tensorflow example with Placeholder value9660.Basic example of Tensorflow with variable9861.How the various activation function perform in tensorflow9962.Basic Linear regression with Tensorflow10163.Classification problem with tensorflow10464.Optimizer performance in tensorflow10765.Classifier with Tensorflow11066.Dropout Loss in Tensorflow11467.What is Keras?11768.Who makes Keras? Contributors and backers11869.What are the Keras user experience?11870.Sequential Model in KERAS11871.Logistic Regression in KERAS12572.MLP Model with KERAS13373.Dropout in KERAS13974.CNN Layer in KERAS14475.LSTM in KERAS150

Télécharger ADVANCED DATA SCIENCE NEURAL NETWORK, TENSORFLOW ,KERA PART 1: Advanced Machine Learning, Data Science, AI, Neural Network, Tensorflow, KERA (English Edition) de GICGAC ACADEMY Livre PDF Gratuit

Keras: the Python deep learning API ~ Exascale machine learning. Built on top of TensorFlow 2.0, . Keras is a central part of the tightly-connected TensorFlow 2.0 ecosystem, covering every step of the machine learning workflow, from data management to hyperparameter training to deployment solutions. State-of-the-art research. Keras is used by CERN, NASA, NIH, and many more scientific organizations around the world (and yes .

Tensorflow - A Neural Network Playground ~ Next, the network is asked to solve a problem, which it attempts to do over and over, each time strengthening the connections that lead to success and diminishing those that lead to failure. For a more detailed introduction to neural networks, Michael Nielsen’s Neural Networks and Deep Learning is a good place to start.

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LSTM by Example using Tensorflow - Towards Data Science ~ Listing 1. A short story from Aesop’s Fables with 112 unique symbols. Words and punctuation marks are both considered symbols. If we feed a LSTM with correct sequences from the text of 3 symbols as inputs and 1 labeled symbol, eventually the neural network will learn to predict the next symbol correctly (Figure 1).

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DeepLearning.AI TensorFlow Developer Professional ~ Offered by DeepLearning.AI. TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models. In this hands-on, four-course Professional Certificate program, you’ll learn the .

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TensorFlow 2 quickstart for beginners / TensorFlow Core ~ Build a neural network that classifies images. Train this neural network. And, finally, evaluate the accuracy of the model. This is a Google Colaboratory notebook file. Python programs are run directly in the browser—a great way to learn and use TensorFlow. To follow this tutorial, run the notebook in Google Colab by clicking the button at .

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Intel® Optimization for TensorFlow* Installation Guide ~ TensorFlow* is a widely-used machine learning framework in the deep learning arena, demanding efficient utilization of computational resources. In order to take full advantage of Intel® architecture and to extract maximum performance, the TensorFlow framework has been optimized using oneAPI Deep Neural Network Library (oneDNN) primitives, a popular performance library for deep learning .

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Dropout Neural Network Layer In - Towards Data Science ~ Code. In the proceeding example, we’ll be using Keras to build a neural network with the goal of recognizing hand written digits. from keras.datasets import mnist from matplotlib import pyplot as plt plt.style.use('dark_background') from keras.models import Sequential from keras.layers import Dense, Flatten, Activation, Dropout from keras.utils import normalize, to_categorical

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PyTorch ~ An open source machine learning framework that accelerates the path from research prototyping to production deployment. Install Prototype Features Now Available - APIs for Hardware Accelerated Mobile and ARM64 Builds. Announcing PyTorch Developer Day. Accelerating Training on NVIDIA GPUs with PyTorch Automatic Mixed Precision. Announcing the Winners of the 2020 Global PyTorch Summer Hackathon .