Build Python Apps with TensorFlow and a Fun Super Tank Game
- Development
- Feb 03, 2025

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
Who Should Attend
Target Audiences
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

Mammoth Interactive
Top-Rated Instructor, 3.3 Million+ Students

John Bura
Best Selling Instructor Web/App/Game Developer 1Mil Students
Rating Distribution
Frequently Asked Questions
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