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Advanced Machine Learning & Data Analysis Projects Bootcamp

Build projects like a text summarizer! Learn object localization, image recognition and structuring data with pandas
Rating: 4.3 out of 54.3 (234 ratings)
24,339 students
Created by Mammoth Interactive, John Bura
Last updated 2/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Code in 3 programming languages: Java, Python and Swift
  • Build nodes and data models for linear regression
  • Use summarizing mechanisms to handle text data
  • Test projects on mobile devices
  • Examine computational graphs
  • Analyze scalars and histograms
  • Build neuron functions
  • Load, convert, and display image and digit data
  • Describe data with statistics
  • And much more...

Requirements

  • PyCharm

Description

"Excellent! Thank you for all your hard work." - Mammoth Interactive student Inderpal

"Great! Well explained and the instructor provides clear examples" - Mark T.

Dive into a world of data science and analysis with a wide range of examples including the CIFAR 100 image dataset, Xcode development for Apple, Swift coding, CoreML, image recognition, and structuring data with pandas.

This Mammoth Interactive course was funded by a #1 project on Kickstarter

Learn Android Studio, Java, app development, Pycharm, Python coding, Tensforflow and more with Mammoth Interactive.

Build advanced projects using machine learning including advanced the MNIST database with neuron functions. Build a text summarizer and learn object localization, object recognition and Tensorboard.

Machine learning is a machine’s ability to make decisions or predictions based on previous exposure to data and extensive training. In other words, if a machine (program, app, etc.) improves its prediction accuracy through training then it has “learned”.

Learn How Models Work

Computational graphs consist of a network of connected nodes (often called neurons). Each of these nodes typically has a weight and a bias that helps determine, given an input, which path is the most likely. 

There are 4 main components to building a machine learning program: data gathering and formatting, model building, training, and testing and evaluating

Data Gathering and Formatting

You will learn to gather plenty of data for the model to learn from.

All data should be formatted pretty much the same (images same size, same color scheme, etc.) and should be labelled. Also divide data into mutually exclusive training and testing sets.

Model Building

You will learn to figure out which kind of model scheme works best and what kinds of algorithms work best for the problem you’re trying to solve.

Training, Testing and Evaluating

The model can choose paths through the neural network or computational graph based upon the inputs for a particular run, as well as the weights and biases of neurons in the network. 

In supervised learning, we show the model what the correct outputs are for a given set of inputs and the model alters the weights and biases of neurons to minimize the difference between its output and the correct answer.

Enroll Now to Learn with Mammoth Interactive

Who this course is for:

  • Topics involve intermediate math, so familiarity with university-level math is very helpful

Course content

30 sections • 132 lectures • 20h 34m total length

  • Preview02:25
  • Project Resources - Mammoth Interactive
    00:02

  • Preview06:44
  • Preview12:12
  • Setting up an Emulator and Running Project
    06:43
  • Code
    00:01

  • Intro to Language Basics
    02:46
  • Variable Types
    14:00
  • Operations on Variables
    10:49
  • Array and Lists
    09:26
  • Array and List Operations
    08:00
  • If and Switch Statements
    11:34
  • While Loops
    10:09
  • For Loops
    08:51
  • Functions Intro
    08:39
  • Parameters and Return Values
    07:05
  • Classes and Objects Intro
    12:14
  • Superclass and Subclasses
    11:42
  • Static Variables and Axis Modifiers
    07:27

  • Intro To Android App Development
    01:57
  • Building Basic UI
    12:15
  • Connecting UI to Backend
    06:12
  • Implementing Backend and Tidying UI
    09:09

  • Introduction to Machine Learning
    01:59
  • Pycharm Files
    00:02

  • Project Overview
    02:40
  • Pycharm Source Files - Mammoth Interactive
    00:02

  • Downloading and Installing Pycharm and Python
    06:55
  • Exploring Pycharm
    07:48

  • Introduction to Variables
    13:17
  • Variables Operations and Conversions
    12:35
  • Collection Types
    12:47
  • Collections Operations
    08:42
  • Control Flow If Statements
    12:50
  • While and For Loops
    10:44
  • Functions
    11:23
  • Classes and Objects
    15:40

  • Project Demo
    02:53
  • Topics List
    06:09
  • Importing Tensorflow to Pycharm
    04:25
  • Constant Nodes and Sessions
    09:01
  • Variable Nodes
    10:46
  • Placeholder Nodes
    07:35
  • Operation nodes
    12:47
  • Loss, Optimizers, and Training
    11:56
  • Building a Linear Regression Model
    20:30
  • Tensorflow Project Files - Mammoth Interactive
    00:02

  • Introduction - Improving Model Efficiency
    05:47
  • Project Code - Mammoth Interactive
    00:02
  • Introduction to Tensorflow Lite
    10:19

Instructors

Mammoth Interactive
Top-Rated Instructor, 700,000+ Students
Mammoth Interactive
  • 4.2 Instructor Rating
  • 10,814 Reviews
  • 218,784 Students
  • 269 Courses

"I absolutely love this course. This is such a comprehensive course that was well worth the money I spent and a lot more. Will definitely be looking at more Mammoth Interactive courses when I finish this." – Student Matt W.

"Very good at explaining the basics then building to more complex features." – Student Kevin L.

Mammoth Interactive has been contracted to produce epic soundtracks, addicting levels, rock solid programming and business development.

John Bura
Best Selling Instructor Web/App/Game Developer 700k Students
John Bura
  • 4.3 Instructor Rating
  • 18,302 Reviews
  • 345,274 Students
  • 301 Courses

John Bura is has been a successful Udemy instructor since 2011. John Bura has been programming games since 1997 and teaching since 2002. John is the owner of the game development studio Mammoth Interactive. This company produces XBOX 360, iPhone, iPad, android, HTML 5, ad-games and more. Mammoth Interactive recently sold a game to Nickelodeon! John has been contracted by many different companies to provide game design, audio, programming, level design and project management. To this day John has 40 commercial games that he has contributed to. Several of the games he has produced have risen to the top 10 in the Apple's app store. In his spare time John likes to play ultimate Frisbee, cycle and work out.

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