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Build Next-Level Apps w TensorFlow, Python Sketch

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  • Apr 18, 2025
SynopsisBuild Next-Level Apps w/ TensorFlow, Python & Sketch, ava...
Build Next-Level Apps w TensorFlow, Python Sketch  No.1

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

  • Build Next-Level Apps w TensorFlow, Python Sketch  No.2
    Mammoth Interactive
    Top-Rated Instructor, 3.3 Million+ Students
  • Build Next-Level Apps w TensorFlow, Python Sketch  No.3
    John Bura
    Best Selling Instructor Web/App/Game Developer 1Mil Students
  • Rating Distribution

  • 1 stars: 0 votes
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  • 3 stars: 1 votes
  • 4 stars: 2 votes
  • 5 stars: 4 votes
  • 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!