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Build Next-Level Apps w/ TensorFlow, Python & Sketch

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Build Next-Level Apps w/ TensorFlow, Python & Sketch, available at $19.99, has an average rating of 4.64, with 165 lectures, based on 7 reviews, and has 114 subscribers.

You will learn about Improve your projects to make faster apps and more accurate models. Build and run Python projects. Build and run Android projects. Wireframe apps and make your own libraries. Create dynamic user interface elements. And more! This course is ideal for individuals who are 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 or Developers who need help with the design portion of their app development process or Anyone who likes art and design and wants to learn a new program to put in their portfolio or Designers who want to add an in-demand user interface designer skill to their resume It is particularly useful for 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 or Developers who need help with the design portion of their app development process or Anyone who likes art and design and wants to learn a new program to put in their portfolio or Designers who want to add an in-demand user interface designer skill to their resume.

Enroll now: Build Next-Level Apps w/ TensorFlow, Python & Sketch

Summary

Title: Build Next-Level Apps w/ TensorFlow, Python & Sketch

Price: $19.99

Average Rating: 4.64

Number of Lectures: 165

Number of Published Lectures: 165

Number of Curriculum Items: 165

Number of Published Curriculum Objects: 165

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Improve your projects to make faster apps and more accurate models.
  • Build and run Python projects.
  • Build and run Android projects.
  • Wireframe apps and make your own libraries.
  • Create dynamic user interface elements.
  • And more!

Who Should Attend

  • 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
  • Developers who need help with the design portion of their app development process
  • Anyone who likes art and design and wants to learn a new program to put in their portfolio
  • Designers who want to add an in-demand user interface designer skill to their resume

Target Audiences

  • 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
  • Developers who need help with the design portion of their app development process
  • Anyone who likes art and design and wants to learn a new program to put in their portfolio
  • Designers who want to add an in-demand user interface designer skill to their resume

Learn to Code and Design for Machine Learning Apps

Discover applications of machine learning and where we use machine learning daily. Design apps, icons, landing pages, and animations with Sketch. And much more.

Funded by a #1 Kickstarter Project

Create your own object-localization, image/text classificiation 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.

  • 15 Supplemental Resources

  • Watch Offline via the Udemy App

  • 21.5 hours on-demand video

  • 18 Articles

  • Full lifetime access

Build Apps with PreBuilt Models

Learn how the TensorFlow estimator differs from other computational graphs. Dive through TensorBoard examples. Learn Python language fundamentals. Learn Java language fundamentals.

Included in this course is material for beginners to get comfortable with the interfaces. Please note that we reuse this content in similar courses because it is introductory material. You can find some material in this course in the following related courses:

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

  • Complete Sketch UI For Beginners: App Design From Scratch!

  • The Machine Learning and App Building Masterclass

Build a User Interface From Scratch

You’ll learn to animate with Anima and Principle, and wireframe mobile apps! By the end of this course, you will be able to build any mobile page you want from practice at log-in pages, main pages, settings pages, and user list pages. You’ll also learn to create icons for apps or other projects.

Landing Pages and Graphics

  • Promote your app with a web landing page

  • Make vector graphics from your drawings or sketches

  • Work faster than ever before with a clean interface and cutting edge techniques

  • Make your own libraries

  • Create dynamic user interface elements

Learn Android, Python and Java

You will learn the basics of languages, programs, and underlying concepts of machine learning. Watch over-the-shoulder style and follow along to build your own machine learning-driven mobile apps.

Learn to Prototype Apps

  • Install Sketch and start projects

  • Use pencils, shapes, artboard, text, color and symbols

  • Find any copyright free image and font you need

  • Create eye enticing color palettes

Machine Learning Models

Explore different machine learning mechanisms and commonly used algorithms. Learn how TensorFlow makes machine learning development easier.

Build a complete computational model. Train and test a model and use it for future predictions. Build a linear regression model to fit a line through data and predict values.

Build apps, learn PyCharm, Android Studio, Machine Learning, TensorFlow models, TensorBoard, and so much more in this epic artificial intelligence course.

Build a Massive Project

You will make numerous pages for an application, including the landing page, log-in page, main page, settings page, and user list page. You will build an app icon. We even cover exporting and prototyping.

Promoting your app is a crucial part if you want to make money as an app developer. We’ll show you how to build a beautiful landing page to display your app.

Enroll Now for Lifetime Access

Course Curriculum

Chapter 1: Introduction to Machine Learning and Software

Lecture 1: Source Files

Chapter 2: Intro to Android

Lecture 1: Intro and Topics List

Chapter 3: Intro to Android Studio

Lecture 1: Downloading and Installing Android Studio

Lecture 2: Exploring Interface

Lecture 3: Setting up an Emulator and Running Project

Chapter 4: 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 5: 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 6: Intro to ML Concepts

Lecture 1: Intro to ML

Lecture 2: Pycharm Files

Chapter 7: Intro to Pycharm

Lecture 1: Intro and Topics List

Lecture 2: Learning Python with Mammoth Interactive

Chapter 8: Introduction

Lecture 1: Downloading and Installing Pycharm and Python

Lecture 2: Exploring Pycharm

Chapter 9: 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 10: Intro to Tensorflow

Lecture 1: 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: Source Files

Chapter 11: Machine Learning in Android Studio Projects

Lecture 1: Introduction to Level 2

Chapter 12: 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 13: 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 14: 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 15: 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 16: Advanced MNIST

Lecture 1: Intro and Demo

Lecture 2: Topics List

Instructors

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Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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