Complete Prediction and Detection Model Building with Python

Course Curriculum

Chapter 1: Introduction to Machine Learning + Software

Lecture 1: Projects Overview

Lecture 2: Prediction and Detection Project Resources – Mammoth Interactive

Chapter 2: Android Studio

Lecture 1: Downloading and Installing Android Studio

Lecture 2: Exploring Interface

Lecture 3: Setting up an Emulator and Running Project

Lecture 4: Code

Chapter 3: Introduction to the Java Programming Language

Lecture 1: Introduction to the Java Programming Language

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

Lecture 10: Parameters and Return Values

Lecture 11: Classes and Objects

Lecture 12: Superclass and Subclasses

Lecture 13: Static Variables and Axis Modifiers

Chapter 4: 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 5: Machine Learning Concepts

Lecture 1: Machine Learning Explained

Lecture 2: Pycharm Files – Mammoth Interactive

Chapter 6: Pycharm Projects Overview

Lecture 1: Project Overview

Lecture 2: Pycharm Source Files – Mammoth Interactive

Chapter 7: Introduction to PyCharm

Lecture 1: Downloading and Installing Pycharm and Python

Lecture 2: Exploring Pycharm

Chapter 8: Python Language Basics

Lecture 1: Introduction 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 9: Beginner's Tensorflow Project

Lecture 1: Project Demo

Lecture 2: Topics List

Lecture 3: Installing TensorFlow

Lecture 4: Importing Tensorflow to Pycharm

Lecture 5: FAQ: Help with TensorFlow Installation

Lecture 6: Constant Nodes and Sessions

Lecture 7: Variable Nodes

Lecture 8: Placeholder Nodes

Lecture 9: Operation nodes

Lecture 10: Loss, Optimizers, and Training

Lecture 11: Building a Linear Regression Model

Lecture 12: Tensorflow Project Files – Mammoth Interactive

Chapter 10: Build Image Recognition Apps

Lecture 1: Introduction to Upcoming Projects

Lecture 2: Source Code – Mammoth Interactive

Chapter 11: Stock Market Prediction

Lecture 1: Project Demo

Lecture 2: Project Overview

Lecture 3: If Receiving JSON Parsing Error

Lecture 4: Retrieving Data via RESTful API Call

Lecture 5: Parsing JSON Data Pycharm Style

Lecture 6: Formatting Data

Lecture 7: Building the Model

Lecture 8: Training and Testing The model

Lecture 9: Freezing Graph

Lecture 10: Setting up Android Project

Lecture 11: Building UI

Lecture 12: Requesting Data Via AsyncTask

Lecture 13: Parsing JSON Data Android Style

Lecture 14: Running Inference and Displaying Results

Lecture 15: Stock Market Prediction Project Files – Mammoth Interactive

Chapter 12: Text Prediction

Lecture 1: Project Demo

Lecture 2: Project Overview

Lecture 3: Processing Text Data

Lecture 4: Building Data Sets and Model Builder Function

Lecture 5: Building Computational Graph

Lecture 6: Writing Training and Testing Code

Lecture 7: Training, Testing, and Freezing Graph

Lecture 8: Setting up Android Project

Lecture 9: Setting Up a User Interface

Lecture 10: Setting up Vocab Dictionary

Lecture 11: Formatting Input and Running Through Model

Lecture 12: Interpreting Results and Summary

Lecture 13: Text Prediction – Mammoth Interactive

Chapter 13: Weather Prediction

Lecture 1: Project Demo

Lecture 2: Project Overview

Lecture 3: Retrieving the Data

Lecture 4: Formatting Datasets

Lecture 5: Building Computational Graph

Lecture 6: Writing Training, Testing, and Evaluating Functions

Lecture 7: Training, Testing, and Freezing the Model

Lecture 8: Setting up Android Project