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Learn how to make a genuine difference in your life by taking our popular Machine Learning for Apps Course. Our commitment to online learning and our technical experience has been put to excellent use within the content of these educational modules. By enrolling today, you can take your knowledge of Machine Learning for Apps to a whole new level and quickly reap the rewards of your study in the field you have chosen.
We are confident that you will find the skills and information that you will need to succeed in this area and excel in the eyes of others. Do not rely on substandard training or half-hearted education. Commit to the best, and we will help you reach your full potential whenever and wherever you need us.
Please note that Machine Learning for Apps provides valuable and significant theoretical training for all. However, it does not offer official qualifications for professional practice. Always check details with the appropriate authorities or management.
By completing the training in Machine Learning for Apps, you will be able to significantly demonstrate your acquired abilities and knowledge of Machine Learning for Apps. This can give you an advantage in career progression, job applications, and personal mastery in this area.
This course is designed to provide an introduction to Machine Learning for Apps and offers an excellent way to gain the vital skills and confidence to start a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Full-time and part-time learners are equally supported, and the study periods are entirely customisable to your needs.
Once you have completed all the modules in the Machine Learning for Apps course, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.
Show off Your New Skills with a Certification of Completion
The learners have to successfully complete the assessment of this Machine Learning for Apps course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. Learners can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.
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 Image VC in Interface Builder / Wiring Up | 00:08:00 | ||
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 | 00:08:00 | ||
Creating Image Cell | 00:08:00 | ||
Creating Food Items Helper File | 00:00:00 | ||
Creating Custom 3×3 Grid UI Collection View Flow Layout | 00:09:00 | ||
Choosing, Downloading, Importing Core ML Model | 00:06:00 | ||
Passing Images through Core ML Model | 00:12:00 | ||
Handling Core ML Prediction Results | 00:10:00 | ||
Challenge –Core ML Photo Analysis | 00:01:00 | ||
Assignment | |||
Assignment – Machine Learning for Apps | 00:00:00 |
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