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Development Data Science Machine Learning

Machine Learning for Apps

Start building more intelligent apps with Machine Learning. Take advantage of this new foundational framework!
Rating: 4.2 out of 54.2 (251 ratings)
11,344 students
Created by Devslopes by Mark Wahlbeck
Last updated 10/2017
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Learn to code how the PROs code - not just copy and paste
  • Build Real Projects - You'll get to build projects that help you retain what you've learned
  • Build awesome apps that can make predictions
  • Build amazing apps that can classify human handwriting

Course content

6 sections • 42 lectures • 6h 52m total length

  • Preview07:46
  • Preview06:34
  • Installing Anaconda / Python Environment
    07:25
  • Downloading / Setting Up Atom & Plugins
    09:02

  • Variables in Python
    08:24
  • Functions, Conditionals, & Loops in Python
    09:50
  • Arrays & Tuples in Python
    13:52
  • Importing Modules in Python
    05:22

  • What is scikit-learn? Why use it?
    03:52
  • Installing scikit-learn & scipy with Anaconda
    03:28
  • Intro to the Iris Dataset
    03:28
  • Datasets: Features & Labels Explained
    07:39
  • Loading the Iris Dataset / Examining & Preparing Data
    09:27
  • Creating / Training a KNeighborsClassifier
    09:42
  • Testing Prediction Accuracy with Test Data
    12:08
  • Building Our Own KNeighborsClassifier
    18:00

  • What is Keras? Why use it?
    08:01
  • What is a Convolutional Neural Network (CNN)?
    26:30
  • Installing Keras with Anaconda
    04:38
  • Preparing Dataset for a CNN
    17:38
  • Building / Visualizing a CNN using Sequential: Part 1
    14:07
  • Building / Visualizing a CNN using Sequential: Part 2
    19:40
  • Training CNN / Evaluating Accuracy / Saving to Disk
    17:53
  • Switching Python Environments / Converting to Core ML Model
    13:39

  • Intro to App – Handwriting
    02:56
  • Building Interface / Wiring Up
    11:42
  • Drawing On Screen
    21:01
  • Importing Core ML Model / Reading Metadata
    05:16
  • Utilizing Core ML / Vision to Make Prediction
    17:31
  • Handling / Displaying Prediction Results
    15:13

  • Intro to App – Core ML Photo Analysis
    04:25
  • What is Machine Learning?
    07:46
  • What is Core ML?
    05:03
  • Creating Xcode Project
    02:43
  • Building ImageVC in Interface Builder / Wiring Up
    07:40
  • Creating ImageCell & Subclass / Wiring Up
    08:13
  • Creating FoodItems Helper File
    07:02
  • Creating Custom 3x3 Grid UICollectionViewFlowLayout
    09:12
  • Choosing, Downloading, Importing Core ML Model
    05:18
  • Passing Images Through Core ML Model
    12:18
  • Handling Core ML Prediction Results
    09:42
  • Challenge – Core ML Photo Analysis
    01:15

Requirements

  • Must have a computer with OSX or macOS on it

Description

MACHINE LEARNING FOR APPS

Welcome to the most comprehensive course on Core ML, one of Apples hot new features for iOS 11. The goal with Machine Learning is to mimic the human mind. It can be used to identify things like objects or images, make predictions and even analyze and identify speech.

Dive in and learn the core concepts of machine learning and start building apps that can think! In this course you going to learn everything you need to know to start building more intelligent apps and your own ML Models.

WHY TAKE THIS COURSE?

Core ML is the first step if you want to start building apps with AI. Machine Learning opens an entirely new world to opportunities that will take your apps to the next level.


Here are some of the things you'll be able to do after taking this course:

  • Learn to code how the PROs code - not just copy and paste
  • Build Real Projects - You'll get to build projects that help you retain what you've learned
  • Build awesome apps that can make predictions
  • Build amazing apps that can classify human handwriting

WHAT YOU WILL LEARN:

  • Learn about the foundation of Machine Learning and Core ML
  • Learn foundational python
  • Build a classification model allow your apps to make predictions
  • Build a neural network for your app that can classify human writing
  • Learn core ML concepts so you can build your own ML Model
  • Utilize the power of Machine Learning and AI for use in iOS apps
  • Learn how to pass in images to Apples pre trained model - MobileNet

Don't forget to join the free live community where you can get free help anytime from other students

Who this course is for:

  • If you have basic experience with iOS development take this course
  • If you have basic experience with iOS or mobile development then take this course

Featured review

Ronald F. Paglinawan
Ronald F. Paglinawan
118 courses
20 reviews
Rating: 5.0 out of 5a year ago
Kaleb is really really great teacher. He's excited what his teaching and explains it very well. I learned a lot creating apps with machine learning on this course! Thanks Kaleb and the team of DevSlopes for creating this course! I hope you create a new version of this course on iOS 12 and CoreML2. :)

Instructor

Devslopes by Mark Wahlbeck
Learn programming & app development
Devslopes by Mark Wahlbeck
  • 4.3 Instructor Rating
  • 51,698 Reviews
  • 331,677 Students
  • 25 Courses

Devslopes transforms beginner students into paid professionals through curated project based videos, interactive quizzes, and exercises.  After completing each course, you will have a strong portfolio, coupled with the technical understanding to build your own custom applications.


Our target students are:

First time developers

Entrepreneurs who want to build their own technology startup

Current developers looking to either advance their careers or learn new technologies.


By taking our courses, our students have been able to:

Get jobs as developers with amazing salaries

Launch (and even sell) their technology startups 

Get promotions and make substantial career changes


We strive to teach students how to code through polished apps inspired by real world examples. We want our students to build projects that they are proud of, that look and operate just like apps they use in their everyday life. 


We are passionate about helping people reveal their hidden talents and guiding them into the exciting world of startups and programming.

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