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Machine Learning for Apps Training Course

4k learners

Dive in and learn the fundamental concepts of machine learning and start developing applications that can think of! In this course, you are going to learn everything you need to know to start building brilliant apps and your Machine Learning models.

  • Access to GreyCampus platform

  • GreyCampus Course completion certificate

Subscribe to this course + 29 courses
USD 50

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Course Overview

Machine Learning is the ability of computers to record the behaviors of operations being conducted through them. After recording they are then able to give out the same output without manual instruction input. Machine learning for Apps means applying this concept to everyday apps as used on computers or mobiles. In this course, you will learn what and how machine learning is used. Also, learn how to apply machine learning using python.

  • 1-year access to audio-video lectures
  • Course completion certificate

Course Outline

  • Introduction to Course
    What is Machine Learning?
    Basics of Machine Learning
    Installing Anaconda / Python Environment
    Downloading / Setting Up Atom & Plugins
  • Python Basics
    Variables in Python
    Arrays & Tuples in Python
    Functions, Conditionals, & Loops in Python
    Importing Modules in Python
  • Building a Classification Model
    What is scikit-learn- Why use it
    Installing scikit-learn & scipy with Anaconda
    Intro to the Iris Dataset
    Datasets- Features & Labels Explained
    Loading the Iris Dataset - Examining & Preparing Data
    Creating - Training a KNeighborsClassifier
    Testing Prediction Accuracy with Test Data
    Building Our Own KNeighbors Classifier
  • Building a Convolutional Neural Network
    What is Keras- Why use it
    What is a Convolutional Neural Network (CNN)
    Installing Keras with Anaconda
    Preparing Dataset for a CNN
    Building - Visualizing a CNN using Sequential- Part 1
    Building - Visualizing a CNN using Sequential- Part 2
    Training CNN - Evaluating Accuracy - Saving to Disk
    Switching Python Environments - Converting to Core ML Model
    • Building a Handwriting Recognition App
      Intro to App – Handwriting
      Building Interface - Wiring Up
      Drawing On Screen
      Importing Core ML Model - Reading Metadata
      Utilizing Core ML - Vision to Make Prediction
      Handling - Displaying Prediction Results
    • Core ML Basics
      Intro to App – Core ML Photo Analysis
      What is Machine Learning
      What is Core ML
      Creating Xcode Project
      Building ImageVC in Interface Builder - Wiring Up
      Creating ImageCell & Subclass - Wiring Up
      Creating FoodItems Helper File
      Creating Custom 3x3 Grid UICollectionViewFlowLayout
      Choosing, Downloading, Importing Core ML Model
      Passing Images Through Core ML Model
      Handling Core ML Prediction Results
      Challenge – Core ML Photo Analysis

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