Up to 52% Off on Machine Learning for Apps - Online Course at Training Express
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You’ll learn how to leverage machine learning algorithms and techniques to enhance your apps, making them smarter, and more efficient.
What you will learn in this course:
Curriculum:
Section 01: Intro to Course
- What is Machine Learning?
- Basics of Machine Learning
- Installing Anaconda / Python Environment
- Downloading / Setting Up Atom and Plugins
Section 02: Python Basics
- Variables in Python
- Functions, Conditionals, and Loops in Python
- Arrays and Tuples in Python
- Importing Modules in Python
Section 03: Building a Classification Model
- What is scikit-learn? Why use it?
- Installing scikit-learn and scipy with Anaconda
- Intro to the Iris Dataset
- Datasets: Features and Labels Explained
- Loading the Iris Dataset / Examining and Preparing Data
- Creating / Training a KNeighborsClassifier
- Testing Prediction Accuracy with Test Data
- Building Our Own KNeighborsClassifie
Section 04: 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
Section 05: 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
Section 06: Core ML Basics
- Intro to App -Core ML Photo Analysis
- What is Machine Learning?
- What is Core ML?
- Creating X code Project
- Building Image VC in Interface Builder / Wiring Up
- Creating Image Cell
- Creating Food Items Helper File
- Creating Custom 3×3 Grid UI Collection View Flow Layout
- Choosing, Downloading, Importing Core ML Model
- Passing Images through Core ML Model
- Handling Core ML Prediction Results
- Challenge –Core ML Photo Analysis
What's included:
- Fully online, interactive course.
- Free PDF certificate on course completion.
- 24/7 access to the course for 1-year.
- Online support.
- CPD Certification
- No hidden fees
Course Link: https://trainingexpress.org.uk/course/machine-learning-for-apps/
You’ll learn how to leverage machine learning algorithms and techniques to enhance your apps, making them smarter, and more efficient.
What you will learn in this course:
Curriculum:
Section 01: Intro to Course
- What is Machine Learning?
- Basics of Machine Learning
- Installing Anaconda / Python Environment
- Downloading / Setting Up Atom and Plugins
Section 02: Python Basics
- Variables in Python
- Functions, Conditionals, and Loops in Python
- Arrays and Tuples in Python
- Importing Modules in Python
Section 03: Building a Classification Model
- What is scikit-learn? Why use it?
- Installing scikit-learn and scipy with Anaconda
- Intro to the Iris Dataset
- Datasets: Features and Labels Explained
- Loading the Iris Dataset / Examining and Preparing Data
- Creating / Training a KNeighborsClassifier
- Testing Prediction Accuracy with Test Data
- Building Our Own KNeighborsClassifie
Section 04: 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
Section 05: 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
Section 06: Core ML Basics
- Intro to App -Core ML Photo Analysis
- What is Machine Learning?
- What is Core ML?
- Creating X code Project
- Building Image VC in Interface Builder / Wiring Up
- Creating Image Cell
- Creating Food Items Helper File
- Creating Custom 3×3 Grid UI Collection View Flow Layout
- Choosing, Downloading, Importing Core ML Model
- Passing Images through Core ML Model
- Handling Core ML Prediction Results
- Challenge –Core ML Photo Analysis
What's included:
- Fully online, interactive course.
- Free PDF certificate on course completion.
- 24/7 access to the course for 1-year.
- Online support.
- CPD Certification
- No hidden fees
Course Link: https://trainingexpress.org.uk/course/machine-learning-for-apps/
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