Master Neural Networks: Build with JavaScript and React
Posted on 01 Sep 13:24 | by BaDshaH | 0 views
Published 9/2024
Duration: 16h24m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 7.84 GB
Genre: eLearning | Language: English
Build and integrate Neural Networks in Web Apps with jаvascript, React, and Node.js. From Scratch with Math Included.
What you'll learn
Understand and implement perceptrons (single neuron) for binary classification
Learn and apply neural network fundamentals in code
Integrate neural networks into web applications using jаvascript and React
Work with large-scale data, understanding and parsing it effectively
Requirements
Basic coding experience in any programming language.
Description
Welcome to
Master Neural Networks: Build with jаvascript and React
. This comprehensive course is designed for anyone looking to understand and build neural networks from the ground up using jаvascript and React.
What You'll Learn
Introduction to Neural Networks
Understand the basics of perceptrons and their similarities to biological neurons.
Learn how perceptrons work at a fundamental level.
Building a Simple Perceptron
Code a perceptron to classify simple objects (e.g., pencils vs. erasers) using hardcoded data.
Implement a basic perceptron from scratch and train it with sample inputs and outputs.
Draw graphs and explain the steps needed, including defining weighted sums and activation functions.
Perceptron for Number Recognition
Advance to coding a perceptron for number recognition using the MNIST dataset to identify if a number is 0 or not.
Train the perceptron using the MNIST dataset, optimizing weights and biases.
Learn techniques to calculate accuracy and handle misclassified data.
Save and export the trained model for use in web applications.
Parsing and Preprocessing MNIST Data
Learn to parse and preprocess MNIST data yourself.
Understand the file formats and the steps needed to convert image data into a usable format for training.
Building a Multi-Layer Perceptron (MLP)
Develop a more complex MLP to recognize digits from 0 to 9.
Implement training algorithms and understand backpropagation.
Explore various activation functions like ReLU and Softmax.
Practical Implementation with jаvascript and React
Integrate neural networks into web applications using jаvascript, React, and Node.js.
Build and deploy full-stack applications featuring neural network capabilities.
Create a React application to test and visualize your models, including drawing on a canvas and making predictions.
Integrate TensorFlow library
Learn to setup Neural networks with TensorFlow
Use Tensorflow to recognize numbers from 0-9
Course Features
Step-by-step coding tutorials with detailed explanations.
Hands-on projects to solidify your understanding.
Graphical visualization of neural network decision boundaries.
Techniques to save and export trained models for real-world applications.
Comprehensive coverage from basic perceptrons to multi-layer perceptrons.
Who this course is for
Beginners who want a comprehensive, step-by-step guide to neural networks
Anyone interested in learning neural networks using jаvascript and React
Web developers looking to enhance their skills with AI
Homepage
https://www.udemy.com/course/master-neural-networks-build-with-javascript-and-react/
https://ddownload.com/meyqwnee7qnc
https://ddownload.com/49br0plqzp5s
https://ddownload.com/qvr0ezaiuxzq
https://ddownload.com/gnfu9sds27ei
https://ddownload.com/msjzkv1qkrk2
https://ddownload.com/3m7n1mzl54i8
https://ddownload.com/iemodjxvfw11
https://ddownload.com/tjajecrchzve
https://ddownload.com/gofaeagwtxhc
https://rapidgator.net/file/fe2232ca34a29129430fd0e72fd435b2
https://rapidgator.net/file/98399c16abab9e4358b7489e1e904e0e
https://rapidgator.net/file/175e7697965ff172e9881bbf77aaf900
https://rapidgator.net/file/5912ed1006a770181c5797a39166cdbd
https://rapidgator.net/file/4c39dd8dd679a478bac3fc9c04b3d7ab
https://rapidgator.net/file/ba82a1d93bd100f0e3a7543277f371f0
https://rapidgator.net/file/f546ab232bf9256817e4c0403f1ce41c
https://rapidgator.net/file/f8044d33f3d4c92b4ac1d3b2a7e51eca
https://rapidgator.net/file/5a1ff0c10d988a072da6b799cdb97cda
Related News
System Comment
Information
Users of Visitor are not allowed to comment this publication.
Facebook Comment
Member Area
Top News