Intro to TensorFlow – For iOS & Android
Intro to TensorFlow – For iOS & Android, available at $19.99, has an average rating of 4.1, with 106 lectures, based on 18 reviews, and has 175 subscribers.
You will learn about Learn everything with examples and practical projects Explore 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 Use PyCharm 2017.2.3 and Android Studio 3 to build apps. Intro to iOS, Xcode, Swift, Core ML, and image recognition This course is ideal for individuals who are Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us It is particularly useful for Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us.
Enroll now: Intro to TensorFlow – For iOS & Android
Summary
Title: Intro to TensorFlow – For iOS & Android
Price: $19.99
Average Rating: 4.1
Number of Lectures: 106
Number of Published Lectures: 106
Number of Curriculum Items: 106
Number of Published Curriculum Objects: 106
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn everything with examples and practical projects
- Explore 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
- Use PyCharm 2017.2.3 and Android Studio 3 to build apps.
- Intro to iOS, Xcode, Swift, Core ML, and image recognition
Who Should Attend
- Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us
Target Audiences
- Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us
This course was funded by a wildly successful Kickstarter
- Explore PyCharm 2017.2.3 and the amazing Python 3.6.2 language
- Explore Android Studio 3 and the Java 8 language
- Discover applications of machine learning and where we use artificial intelligence and algorithms daily
- Learn what TensorFlow 1.4.1 is and how it makes machine learning development easier
- Build a linear regression model to fit a line through data
- Learn how to incorporate machine learning models into Android apps
- Build a simple digit recognition project using the MNIST handwritten digit database
- Learn how the TensorFlow estimator differs from other computational graphs
A machine learning framework for everyone
If 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 first
There 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 andexpand 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 required
We 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 demandthan supply
Enroll now to start the next step of your career
Course Curriculum
Lecture 1: Course Trailer
Chapter 1: Update! Resources
Lecture 1: Update! Resources
Chapter 2: Intro to Android Studio
Lecture 1: Intro to Android
Lecture 2: Downloading & Installing Android Studio
Lecture 3: Exploring Interface
Lecture 4: Setting up Emulator and Running Project
Chapter 3: Intro to Java
Lecture 1: Java Language Basics
Lecture 2: Variable Types
Lecture 3: Operations on Variables
Lecture 4: Arrays 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 4: Intro to App Development
Lecture 1: Intro to Android App Development
Lecture 2: Building User Interface
Lecture 3: Connecting UI to Backend
Lecture 4: Implementing Backend and Tidying UI
Chapter 5: Intro to Machine Learning Concepts
Lecture 1: ML Concepts Intro
Lecture 2: Intro to PyCharm
Lecture 3: Installing PyCharm and Python
Lecture 4: Exploring PyCharm
Lecture 5: (Files) Source Code
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
Lecture 9: (Files) Source Code
Chapter 7: Intro to TensorFlow
Lecture 1: TensorFlow Intro
Lecture 2: Topics List
Lecture 3: Importing TensorFlow to PyCharm
Lecture 4: Constant Nodes and Sessions
Lecture 5: Variable Nodes
Lecture 6: Placeholder Nodes
Lecture 7: Operation Nodes
Lecture 8: Loss, Optimizers, and Training
Lecture 9: Building a Linear Regression Model
Lecture 10: (Files) Source Code
Chapter 8: Machine Learning in Android Studio Projects
Lecture 1: Introduction to ML for Android
Chapter 9: Introduction to TensorFlow Estimator
Lecture 1: Introduction to TensorFlow Estimator
Lecture 2: Topics List
Lecture 3: Setting up Prebuilt Estimator Model
Lecture 4: Evaluating and Predicting with Model
Lecture 5: Building Custom Estimator Function
Lecture 6: Testing Custom Estimator Function
Lecture 7: Summary and Model Comparison
Lecture 8: Source Code
Chapter 10: Intro to Android ML Model Import
Lecture 1: Intro & Demo: Android ML Model Import
Lecture 2: Topics List
Lecture 3: Formatting and Saving Model
Lecture 4: Saving Optimized Graph File
Lecture 5: Starting Android Project
Lecture 6: Building UI
Lecture 7: Implementing Inference Functionality
Lecture 8: Testing and Error Fixing
Lecture 9: Source Files
Chapter 11: Simple MNIST
Lecture 1: Intro & Demo: Simple MNIST
Lecture 2: Topics List and Intro to MNIST Data
Lecture 3: Building Computational Graph
Lecture 4: Training and Testing Model
Lecture 5: Saving Graph for Android Import
Lecture 6: Setting up Android Studio Project
Lecture 7: Building User Interface
Lecture 8: Loading Digit Images
Lecture 9: Formatting Image Data
Lecture 10: Making Prediction Using Model
Lecture 11: Displaying Results and Summary
Lecture 12: Source Files
Chapter 12: MNIST With Estimator
Lecture 1: MNIST With Estimator Intro
Lecture 2: Topics List
Lecture 3: Building Custom Estimator Function
Lecture 4: Training & Testing Input Functions
Lecture 5: Predicting Using Model & Comparisons
Lecture 6: Source Files
Chapter 13: Xcode Intro
Lecture 1: Downloading and Installing Xcode
Lecture 2: Don't Have a Mac Computer?
Lecture 3: Exploring XCode's Interface
Chapter 14: Swift Language Basics
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: 2 votes
- 2 stars: 1 votes
- 3 stars: 0 votes
- 4 stars: 8 votes
- 5 stars: 7 votes
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