Hands-On Machine Learning: Learn Tensorflow, Python, & Java!

Jump into a field with more demand than supply. Apps driven by machine learning are the future of mobile app development

What you'll learn
Learn to code in Python and Java
Learn to use PyCharm and Android Studio
Learn to use TensorFlow to build, train, and test machine learning models
Build apps
Understand and expand on machine learning concepts for your own projects
Get tools to work in the future of the world around us as artificial intelligence becomes more prevalent in everything we do
Requirements
No prior experience necessary
We will take you through the steps of downloading and installing Android Studio, PyCharm, and Python
Description
Python, Java, PyCharm, Android Studio and MNIST. Learn to code and build apps! Use machine learning models in hands-on projects.  A wildly successful Kickstarter funded this courseExplore machine learning concepts. Learn how to use TensorFlow 1.4.1 to build, train, and test machine learning models. We explore Python 3.6.2 and Java 8 languages, and how to use PyCharm 2017.2.3 and Android Studio 3 to build apps. A machine learning framework for everyoneIf you want to build sophisticated and intelligent mobile apps or simply want to know more about how machine learning works in a mobile environment, this course is for you.Be one of the firstThere are next to no courses on big platforms that focus on mobile machine learning in particular. All of them focus specifically on machine learning for a desktop or laptop environment.We provide clear, concise explanations at each step along the way so that viewers can not only replicate, but also understand and expand upon what I teach. Other courses don’t do a great job of explaining exactly what is going on at each step in the process and why we choose to build models the way we do. No prior knowledge is requiredWe will teach you all you need to know about the languages, software and technologies we use. If you have lots of experience building machine learning apps, you may find this course a little slow because it’s designed for beginners.Jump into a field that has more demand than supplyMachine learning changes everything. It’s bringing us self-driving cars, facial recognition and artificial intelligence. And the best part is: anyone can create such innovations."This course is GREAT! This is what I want!" – Rated 5 Stars by Mammoth Interactive StudentsEnroll Now While On Sale

Overview

Section 1: Update! Resources

Lecture 1 Resources

Section 2: Intro to Android Studio

Lecture 2 Intro to Android and Topics List

Lecture 3 Downloading and Installing Android Studio

Lecture 4 Exploring Interface

Lecture 5 Setting up Emulator and Running Project

Section 3: Intro to Java

Lecture 6 Java Language Basics

Lecture 7 Variable Types

Lecture 8 Operations on Variables

Lecture 9 Arrays and Lists

Lecture 10 Array and List Operations

Lecture 11 If and Switch Statements

Lecture 12 While Loops

Lecture 13 For Loops

Lecture 14 Functions Intro

Lecture 15 Parameters and Return Values

Lecture 16 Classes and Objects Intro

Lecture 17 Superclass and Subclasses

Lecture 18 Static Variables and Axis Modifiers

Section 4: Intro to App Development

Lecture 19 Intro to Android App Development

Lecture 20 Building Basic User Interface

Lecture 21 Connecting UI to Backend

Lecture 22 Implementing Backend and Tidying UI

Section 5: Intro to ML Concepts

Lecture 23 ML Concepts Intro

Lecture 24 Intro to PyCharm and Topics List

Lecture 25 Installing PyCharm and Python

Lecture 26 Exploring PyCharm

Lecture 27 (Files) Source Code

Section 6: Python Language Basics

Lecture 28 Intro to Variables

Lecture 29 Variables Operations and Conversions

Lecture 30 Collection Types

Lecture 31 Collections Operations

Lecture 32 Control Flow: If Statements

Lecture 33 While and For Loops

Lecture 34 Functions

Lecture 35 Classes and Objects

Lecture 36 (Files) Source Code

Section 7: Intro to TensorFlow

Lecture 37 TensorFlow Intro

Lecture 38 Topics List

Lecture 39 Installing TensorFlow

Lecture 40 FAQ: Help with TensorFlow Installation

Lecture 41 Importing TensorFlow to PyCharm

Lecture 42 Constant Nodes and Sessions

Lecture 43 Variable Nodes

Lecture 44 Placeholder Nodes

Lecture 45 Operation Nodes

Lecture 46 Loss, Optimizers, and Training

Lecture 47 Building a Linear Regression Model

Lecture 48 (Files) Source Code

Section 8: Simple MNIST

Lecture 49 Simple MNIST Intro and Demo

Lecture 50 Topics List and Intro to MNIST Data

Lecture 51 Building Computational Graph

Lecture 52 Training and Testing the Model

Lecture 53 Save & Freeze Graph for Android Import

Lecture 54 Setting up Android Studio Project

Lecture 55 Building User Interface

Lecture 56 Loading Digit Images

Lecture 57 Formatting Image Data

Lecture 58 Making Prediction Using Model

Lecture 59 Displaying Results and Summary

Lecture 60 (Files) Source Code

Lecture 61 Please rate this course

Lecture 62 Bonus Lecture: Newsletter

Anyone who wants to use machine learning in a mobile environment