Learn how to build intelligent handwriting recognition apps from scratch using Python and Core ML
Deepen your knowledge of machine learning and recent developments in the field
Take your Python programming skills to the next level in no time
Know best practices for building a convolutional neural network
Gain an in-depth understanding of the core ML basics
Understand how to build a classification model
Be able to test prediction accuracy with test data
Course Overview
Machine learning as a programming technique has shaped the future of technology. In this course, you will learn how to build intelligent handwriting recognition apps from scratch using Python and Core ML.
The Machine Learning for Apps Level 4 course will teach you how to take advantage of machine learning to code like a pro and build incredible apps that can make predictions. Designed by industry experts, it covers best practices for managing projects, core concepts for creating your own ML model, building a convolutional neural network, and much more.
On successful completion, you will be able to build an amazing handwriting recognition app and convolutional neural network from scratch, and have an in-depth understanding of the core ML basics. This course is ideal for those with a basic understanding of iOS development.
This best selling Machine Learning for Apps Level 4 has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Machine Learning for Apps Level 4 is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.
The Machine Learning for Apps Level 4 is CPD-accredited, so you can be confident you’re completing a quality training course will boost your CV and enhance your career potential. The Machine Learning for Apps Level 4 is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.
After successfully completing the Machine Learning for Apps Level 4, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Machine Learning for Apps Level 4 will help you stand out from the crowd. You can also validate your certification on our website.
We know that you are busy and that time is precious, so we have designed the Machine Learning for Apps Level 4 to be completed at your own pace, whether that’s part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.
Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.
Preview
Certification
After successfully completing the course, you will be able to get the UK and internationally accepted certificate to share your achievement with potential employers or include it in your CV. The PDF Certificate + Transcript is available at £6.99 (Special Offer - 50% OFF). In addition, you can get a hard copy of your certificate for £12 (Shipping cost inside the UK is free, and outside the UK is £9.99).
Course Curriculum
Section 01: Intro to Course
What is Machine Learning?
00:08:00
Basics of Machine Learning
00:07:00
Installing Anaconda / Python Environment
00:07:00
Downloading / Setting Up Atom and Plugins
00:09:00
Section 02: Python Basics
Variables in Python
00:08:00
Functions, Conditionals, and Loops in Python
00:10:00
Arrays and Tuples in Python
00:14:00
Importing Modules in Python
00:05:00
Section 03: Building a Classification Model
What is scikit-learn? Why use it?
00:04:00
Installing scikit-learn and scipy with Anaconda
00:03:00
Intro to the Iris Dataset
00:03:00
Datasets: Features and Labels Explained
00:08:00
Loading the Iris Dataset / Examining and Preparing Data
00:09:00
Creating / Training a KNeighborsClassifier
00:10:00
Testing Prediction Accuracy with Test Data
00:12:00
Building Our Own KNeighborsClassifie
00:18:00
Section 04: Building a Convolutional Neural Network
What is Keras? Why use it?
00:08:00
What is a Convolutional Neural Network (CNN)?
00:27:00
Installing Keras with Anaconda
00:05:00
Preparing Dataset for a CNN
00:18:00
Building / Visualizing a CNN using Sequential: Part 1
00:14:00
Building / Visualizing a CNN using Sequential: Part 2
00:20:00
Training CNN / Evaluating Accuracy / Saving to Disk
00:18:00
Switching Python Environments / Converting to Core ML Model
00:14:00
Section 05: Building a Handwriting Recognition App
Intro to App-Handwriting
00:03:00
Building Interface / Wiring Up
00:12:00
Drawing on Screen
00:21:00
Importing Core ML Model / Reading Metadata
00:05:00
Utilizing Core ML / Vision to Make Prediction
00:18:00
Handling / Displaying Prediction Results
00:15:00
Section 06: Core ML Basics
Intro to App -Core ML Photo Analysis
00:04:00
What is Machine Learning?
00:08:00
What is Core ML?
00:05:00
Creating X code Project
00:03:00
Building Image VC in Interface Builder / Wiring Up
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