Deep Learning with Tensorflow and Angular 2!

Deep Learning with Tensorflow and Angular 2!, available at $59.99, has an average rating of 4.31, with 413 lectures, based on 8 reviews, and has 213 subscribers.

You will learn about Be able to build a simple app with Angular 2 Understand how JavaScript frameworks function Understand programming fundamentals Build 3 apps with pre built models: object-localization, image/text classification, and text summarizer. Import a model built in PyCharm into Android Studio with a multi-step process. Build a simple digit recognition project using the MNIST handwritten digit database?. Discover applications of machine learning and where we use machine learning daily. Explore different machine learning mechanisms and commonly used algorithms. Learn how TensorFlow makes machine learning development easier This course is ideal for individuals who are People that want to learn about Web development at a beginner level or People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow or Anyone who wants to learn the technology that is shaping how we interact with the world around us or Anyone who wants to use data for prediction, recognition, and classification It is particularly useful for People that want to learn about Web development at a beginner level or People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow or Anyone who wants to learn the technology that is shaping how we interact with the world around us or Anyone who wants to use data for prediction, recognition, and classification.

Enroll now: Deep Learning with Tensorflow and Angular 2!

Summary

Title: Deep Learning with Tensorflow and Angular 2!

Price: $59.99

Average Rating: 4.31

Number of Lectures: 413

Number of Published Lectures: 413

Number of Curriculum Items: 413

Number of Published Curriculum Objects: 413

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Be able to build a simple app with Angular 2

Understand how JavaScript frameworks function

Understand programming fundamentals

Build 3 apps with pre built models: object-localization, image/text classification, and text summarizer. Import a model built in PyCharm into Android Studio with a multi-step process. Build a simple digit recognition project using the MNIST handwritten digit database?.

Discover applications of machine learning and where we use machine learning daily. Explore different machine learning mechanisms and commonly used algorithms. Learn how TensorFlow makes machine learning development easier

Who Should Attend

People that want to learn about Web development at a beginner level

People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow

Anyone who wants to learn the technology that is shaping how we interact with the world around us

Anyone who wants to use data for prediction, recognition, and classification

Target Audiences

People that want to learn about Web development at a beginner level

People who want to learn machine learning concepts through practical projects with PyCharm, Python, Android Studio, Java, and TensorFlow

Anyone who wants to learn the technology that is shaping how we interact with the world around us

Anyone who wants to use data for prediction, recognition, and classification

Do you want to learn about Web Development and Machine learning at the same time? With this course you can do exactly that and more!

This course was funded by a wildly successful Kickstarter

With the Deep Learning of Angular 2 and Tensorflow, You will learn about Javascript frameworks for creating websites and create Apps driven by Machine Learning by learning Tensorflow as well as PyCharm, Python, Android Studio and more!

About Tensorflow: ??We use frameworks like TensorFlow that make it easy to build, train, test, and use machine learning models. TensorFlow makes machine learning so much more accessible to programmers everywhere

You can expect a complete and comprehensive course that guides you first through the basics, then through some simple models. You will end up with a ?portfolio of apps driven by machine learning, as well as the know-how to create more and expand upon what we build together.

About Angular 2: ??JavaScript is one of the fundamental languages of the web. JavaScript is easy to program in but some tasks are difficult. JavaScript frameworks are built to make these difficult tasks easier. In this course you will learn how to code with ?Angular.js 2,?? ?a powerful framework that makes building web apps a breeze??. In this course you will learn web programming fundamentals and other valuable skill boosting career knowledge.

This course is ?project based?? so you will not be learning a bunch of useless coding practices. At the end of this course you will have real world apps to use in your portfolio. We feel that project based training content is the best way to get from A to B. Taking this course means that you learn practical, employable ?skills immediately.

Also, now included in this course are bonus courses of other related topics, such as C# and Java! You get more content at a great price!

Enroll now to join the Mammoth community!

Course Curriculum

Chapter 1: Intro to Android Studio

Lecture 1: Intro and Topics List

Lecture 2: Downloading and Installing Android Studio

Lecture 3: Exploring Interface

Lecture 4: Setting up an Emulator and Running Project

Lecture 5: Source Code

Chapter 2: Intro to Java

Lecture 1: Intro to Language Basics

Lecture 2: Variable Types

Lecture 3: Operations on Variables

Lecture 4: Array and Lists

Lecture 5: Array and List Operations

Lecture 6: If and Switch Statements

Lecture 7: While Loops

Lecture 8: For Loops

Lecture 9: Functions Intro

Lecture 10: Parameters and Return Values

Lecture 11: Classes and Objects Intro

Lecture 12: Superclass and Subclasses

Lecture 13: Static Variables and Axis Modifiers

Chapter 3: Intro to App Development

Lecture 1: Intro To Android App Development

Lecture 2: Building Basic UI

Lecture 3: Connecting UI to Backend

Lecture 4: Implementing Backend and Tidying UI

Chapter 4: Intro to ML Concepts

Lecture 1: Intro to ML

Lecture 2: Pycharm_Files

Chapter 5: Introduction to PyCharm for Python

Lecture 1: Intro and Topics List

Lecture 2: Downloading and Installing Pycharm and Python

Lecture 3: Exploring the Pycharm Interface

Lecture 4: Support for Python Problems or Questions

Lecture 5: Learning Python with Mammoth Interactive

Chapter 6: Python Language Basics

Lecture 1: Intro to Variables

Lecture 2: Variables Operations and Conversions

Lecture 3: Collection Types

Lecture 4: Collections Operations

Lecture 5: Control Flow If Statements

Lecture 6: While and For Loops

Lecture 7: Functions

Lecture 8: Classes and Objects

Chapter 7: Intro to Tensorflow

Lecture 1: Intro

Lecture 2: Topics List

Lecture 3: Installing TensorFlow

Lecture 4: Importing Tensorflow to Pycharm

Lecture 5: Constant Nodes and Sessions

Lecture 6: Constant Nodes and Sessions Part 2

Lecture 7: Variable Nodes

Lecture 8: Placeholder Nodes

Lecture 9: Operation nodes

Lecture 10: Loss, Optimizers, and Training

Lecture 11: Building a Linear Regression Model

Lecture 12: Source Files

Chapter 8: Machine Learning in Android Studio Projects

Lecture 1: Coming Up – Machine Learning in Android Studio Projects

Chapter 9: Tensorflow Estimator

Lecture 1: Introduction

Lecture 2: Topics List

Lecture 3: Setting up Prebuilt Estimator Model

Lecture 4: Evaluating and Predicting with Prebuilt Model

Lecture 5: Building Custom Estimator Function

Lecture 6: Testing the Custom Estimator Function

Lecture 7: Summary and Model Comparison

Lecture 8: Source Files

Chapter 10: Intro to Android Machine Learning Model Import

Lecture 1: Intro and Demo

Lecture 2: Topics List

Lecture 3: Formatting and Saving the Model

Lecture 4: Saving the Optimized Graph File

Lecture 5: Starting Android Project

Lecture 6: Building the UI

Lecture 7: Implementing Inference Functionality

Lecture 8: Testing and Error Fixing

Lecture 9: Source Files

Chapter 11: Simple MNIST

Lecture 1: Intro and Demo

Lecture 2: Topics List and Intro to MNIST Data

Lecture 3: Building Computational Graph

Lecture 4: Training and Testing the Model

Lecture 5: Saving and Freezing the Graph for Android Import

Lecture 6: Setting up Android Studio Project

Lecture 7: Building the UI

Lecture 8: Loading Digit Images

Lecture 9: Formatting Image Data

Lecture 10: Making Prediction Using Model

Lecture 11: Displaying Results and Summary

Lecture 12: Simple MNIST – Mammoth Interactive

Chapter 12: MNIST with Estimator

Lecture 1: Introduction

Lecture 2: Topics List

Lecture 3: Building Custom Estimator Function

Lecture 4: Building Input Functions, Training, and Testing

Lecture 5: Predicting Using Our Model and Model Comparisons

Lecture 6: MNIST With Estimator – Mammoth Interactive

Chapter 13: Advanced MNIST

Lecture 1: Intro and Demo

Lecture 2: Topics List

Instructors

Mammoth Interactive
Top-Rated Instructor, 3.3 Million+ Students

John Bura
Best Selling Instructor Web/App/Game Developer 1Mil Students

Rating Distribution

1 stars: 0 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 3 votes

5 stars: 3 votes

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