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Build Python Apps with TensorFlow and a Fun Super Tank Game

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  • Feb 03, 2025
SynopsisBuild Python Apps with TensorFlow and a Fun Super Tank Game,...
Build Python Apps with TensorFlow and a Fun Super Tank Game  No.1

Build Python Apps with TensorFlow and a Fun Super Tank Game, available at $49.99, has an average rating of 4.5, with 166 lectures, based on 5 reviews, and has 97 subscribers.

You will learn about Explore PyCharm and the amazing Python 3 language! Explore Android Studio 3?and the Java 8 language. Make machine learning development easier with TensorFlow. Build a linear regression model to fit a line through data. 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. Build 2D games in Unity. Use pathfinding algorithms to move characters in games. And much more! 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! or Anyone who wants to make games or apps. or Anyone who wants to make games with smart automated features. It is particularly useful for Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us! or Anyone who wants to make games or apps. or Anyone who wants to make games with smart automated features.

Enroll now: Build Python Apps with TensorFlow and a Fun Super Tank Game

Summary

Title: Build Python Apps with TensorFlow and a Fun Super Tank Game

Price: $49.99

Average Rating: 4.5

Number of Lectures: 166

Number of Published Lectures: 166

Number of Curriculum Items: 166

Number of Published Curriculum Objects: 166

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Explore PyCharm and the amazing Python 3 language!
  • Explore Android Studio 3?and the Java 8 language.
  • Make machine learning development easier with TensorFlow.
  • Build a linear regression model to fit a line through data.
  • 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.
  • Build 2D games in Unity.
  • Use pathfinding algorithms to move characters in games.
  • And much more!
  • Who Should Attend

  • Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us!
  • Anyone who wants to make games or apps.
  • Anyone who wants to make games with smart automated features.
  • Target Audiences

  • Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us!
  • Anyone who wants to make games or apps.
  • Anyone who wants to make games with smart automated features.
  • Do you want to build artificial intelligence, machine learning & coding projects?This course is for you! Learn to make apps and an awesome 2D tank game with computer science!

    Funded by a #1 Kickstarter Project by Mammoth Interactive!

    Explore Python, Java, PyCharm and databases. Learn artificial intelligence, use the a star algorithm & code in C#. Discover applications of machine learning and where we use artificial intelligence and algorithms daily.

  • 166 Lectures

  • 24.5 hours on-demand video

  • Watch Offline via the Udemy App

  • 17 Articles

  • 11 Supplemental Resources

  • Full lifetime access

  • Learn How Machine Learning Works

    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.

    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!

  • Learn artificial intelligence by building games and apps

  • ?The Complete 2D Unity & AI for Games with Algorithms Course

  • Learn Unity AI by Making a Tank Game?!

  • Build Machine Learning Models with Data

    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.?

    Everyone Is Welcome!

    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 High Demand Field

    Machine 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.

    Build Unity Games and Code in C#

  • Make a game that uses artificial intelligence!

  • Use a pathfinding algorithm called ‘A Star’ to build a Unity game.?

  • Program artificial intelligence players to think on their own.

  • Discover the Power of Algorithms

    The A* is the base algorithm for path finding. A* is artificial intelligence that will find a path. This algorithm has existed for decades. A* is also important to avoid dangers like a cliff while getting to a destination. As well – suppose a game’s level has two paths.? You can use A* in many different platforms, programming languages and more.

    Learn artificial intelligence by building games and apps

    With the A Star algorithm, game characters can choose a better path to avoid monsters and other obstacles. A Super Tank on a maze will find the best way to go to a point you click. The tank will collect objects along its path.

    The power of this algorithm will push your games to the next level.

    Enroll Now While On Sale!

    Course Curriculum

    Chapter 1: Introduction to Machine Learning and Software

    Lecture 1: Code

    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 to TensorFlow

    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 Upcoming Projects

    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: Xcode Introduction

    Lecture 1: Introduction to iOS

    Lecture 2: Downloading and Installing Xcode

    Instructors

  • Build Python Apps with TensorFlow and a Fun Super Tank Game  No.2
    Mammoth Interactive
    Top-Rated Instructor, 3.3 Million+ Students
  • Build Python Apps with TensorFlow and a Fun Super Tank Game  No.3
    John Bura
    Best Selling Instructor Web/App/Game Developer 1Mil Students
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  • 4 stars: 3 votes
  • 5 stars: 2 votes
  • Frequently Asked Questions

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