Главная
Study mode:
on
1
Keras with TensorFlow Prerequisites - Getting Started With Neural Networks
2
TensorFlow and Keras GPU Support - CUDA GPU Setup
3
Keras with TensorFlow - Data Processing for Neural Network Training
4
Create an Artificial Neural Network with TensorFlow's Keras API
5
Train an Artificial Neural Network with TensorFlow's Keras API
6
Build a Validation Set With TensorFlow's Keras API
7
Neural Network Predictions with TensorFlow's Keras API
8
Create a Confusion Matrix for Neural Network Predictions
9
Save and Load a Model with TensorFlow's Keras API
10
Image Preparation for Convolutional Neural Networks with TensorFlow's Keras API
11
Code Update for CNN Training with TensorFlow's Keras API
12
Build and Train a Convolutional Neural Network with TensorFlow's Keras API
13
Convolutional Neural Network Predictions with TensorFlow's Keras API
14
Build a Fine-Tuned Neural Network with TensorFlow's Keras API
15
Train a Fine-Tuned Neural Network with TensorFlow's Keras API
16
Predict with a Fine-Tuned Neural Network with TensorFlow's Keras API
17
MobileNet Image Classification with TensorFlow's Keras API
18
Process Images for Fine-Tuned MobileNet with TensorFlow's Keras API
19
Fine-Tuning MobileNet on Custom Data Set with TensorFlow's Keras API
20
Data Augmentation with TensorFlow's Keras API
21
Mapping Keras labels to image classes
22
Reproducible results with Keras
23
Initializing and Accessing Bias with Keras
24
Learnable parameters ("trainable params") in a Keras model
25
Learnable parameters ("trainable params") in a Keras Convolutional Neural Network
26
Deploy Keras Neural Network to Flask web service | Part 1 - Overview
27
Deploy Keras neural network to Flask web service | Part 2 - Build your first Flask app
28
Deploy Keras neural network to Flask web service | Part 3 - Send and Receive Data with Flask
29
Deploy Keras neural network to Flask web service | Part 4 - Build a front end web application
30
Deploy Keras neural network to Flask web service | Part 5 - Host VGG16 model with Flask
31
Deploy Keras neural network to Flask web service | Part 6 - Build web app to send images to VGG16
32
Deploy Keras neural network to Flask web service | Part 7 - Visualizations with D3, DC, Crossfilter
33
Deploy Keras neural network to Flask web service | Part 8 - Access model from Powershell, Curl
34
Deploy Keras neural network to Flask web service | Part 9 - Information Privacy, Data Protection
35
TensorFlow.js - Introducing deep learning with client-side neural networks
36
TensorFlow.js - Convert Keras model to Layers API format
37
TensorFlow.js - Serve deep learning models with Node.js and Express
38
TensorFlow.js - Building the UI for neural network web app
39
TensorFlow.js - Loading the model into a neural network web app
40
TensorFlow.js - Explore tensor operations through VGG16 preprocessing
41
TensorFlow.js - Examining tensors with the debugger
42
Broadcasting Explained - Tensors for Deep Learning and Neural Networks
43
TensorFlow.js - Running MobileNet in the browser
Description:
Learn to build, train, and deploy deep learning models using Keras, a powerful neural network API for Python. Master data preprocessing, artificial neural network construction, convolutional neural networks (CNNs), transfer learning, and model deployment techniques. Explore GPU support, data augmentation, and reproducibility in neural networks. Implement web services with Flask, create front-end applications, and utilize TensorFlow.js for client-side neural networks. Gain hands-on experience with popular architectures like MobileNet and VGG16, while diving into tensor operations, broadcasting, and debugging techniques essential for deep learning projects.

Python Deep Learning Neural Network API

Add to list