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


Homepage

https://www.udemy.com/course/mobilemachinelearning/