Building Machine Learning App Interface
This free online course examines how to build a handwriting recognition app, as well as basics of core machine learning.Publisher: YouAccel Training
CertificationView course modules
Machine learning is basically a way that our programs and applications can learn from various data that has been passed into our application. Making predictions, based on the information that was received. A great way to use deep learning to classify images is to build a Convolutional Neural Network (CNN). The Keras library in Python makes it pretty simple to build a CNN. Building Machine Learning App Interface is a free online course that introduces you to Keras. This course teaches you the uses of Keras. You will learn the difference between tensor flow and Keras. A dataset in machine learning is, quite simply, a collection of data pieces that can be treated by a computer as a single unit for analytic and prediction purposes. This means that the data collected should be made uniform and understandable for a machine that doesn't see data the same way as humans do. This course explains how Convolutional Neural Network works and how to classify images.
Next, in this course, you will learn how to run values through convolutional layers, and all the cool processing you need to do. It describes how to build your Convolutional Neural Network using Keras. The goal of 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. This course teaches you how to build an app that can recognize handwriting using the core ML module. It uncovers the process of importing the core ML model to a project in order to use it. This course teaches you how to perform OCR handwriting recognition using OpenCV, Keras, and TensorFlow. You will understand the process involved in making a prediction using a Core ML module to create a request handler. This course teaches you how to handle the result given from Core ML and use the result to cycle through. You will discover what is required in order to determine what number you are actually predicting.
Finally, in this course, you are going to learn everything you need to know to start building more intelligent apps and your own ML models. Core ML is the foundation for domain-specific frameworks and functionality. Core ML supports Vision for analyzing images, Natural Language for processing text. Core ML also supports Speech for converting audio to text, and Sound Analysis for identifying sounds in audio. This course will introduce you to Core Machine Learning, how it works, and how to properly use Core Machine Learning. This course gives you hands-on knowledge on how to correctly integrate Machine Learning into iOS Apps. In this course, you will be guided on how to make a custom UI collection view flow layout. This course will be of immense benefit to website and application developers. Digital or data analysts seeking basic knowledge using the Python environment as well as anyone with basic knowledge of the Python Environment can study this course. Register and Get Started Now!Start Course Now
Building A Convolutional Neutral Network
Building A Conventional Neural Network - Learning Outcomes
Use Of Keras And CNN Dataset
Machine Learning Accuracy
Building A Conventional Neural Network - Lesson Summary
Building A Handwriting Recognition App
Building A Hand Writing Recognition App - Learning Outcomes
Building Hand Writing Recognition App - Lesson Summary
Core Machine Learning Basics
Core Machine Learning Basics - Learning Outcomes
Core Machine Learning Analysis
Image Cell and Helper File
Machine Learning Layout
ML Prediction And Photo Analysis
Core Machine Learning Basics - Lesson Summary
Upon the successful completion of this course, you should be able to:
- Differentiate between Tensor Flow and Keras.
- Explain how Convolutional Neural Network works.
- Discuss how to classify images and how to install Anaconda with Keras.
- Explain how to build an app that can recognize handwriting using the core ML module.
- Summarize how to perform OCR handwriting recognition using OpenCV, Keras, and TensorFlow.
- Discuss how to set up the environment to enable you to draw on your screen.
- Analyze Machine Learning, and how it works.
- Outline the uses of Machine Learning.
- Explain the process of integrating Machine Learning into iOS Apps.
All Alison courses are free to enrol, study and complete. To successfully complete this Certificate course and become an Alison Graduate, you need to achieve 80% or higher in each course assessment. Once you have completed this Certificate course, you have the option to acquire an official Certificate, which is a great way to share your achievement with the world. Your Alison Certificate is:
Ideal for sharing with potential employers - include it in your CV, professional social media profiles and job applications
An indication of your commitment to continuously learn, upskill and achieve high results
An incentive for you to continue empowering yourself through lifelong learning
Alison offers 3 types of Certificates for completed Certificate courses:
Digital Certificate - a downloadable Certificate in PDF format, immediately available to you when you complete your purchase
Certificate - a physical version of your officially branded and security-marked Certificate, posted to you with FREE shipping
Framed Certificate - a physical version of your officially branded and security-marked Certificate in a stylish frame, posted to you with FREE shipping
All Certificates are available to purchase through the Alison Shop. For more information on purchasing Alison Certificates, please visit our FAQs. If you decide not to purchase your Alison Certificate, you can still demonstrate your achievement by sharing your Learner Record or Learner Achievement Verification, both of which are accessible from your Dashboard. For more details on our Certificate pricing, please visit our Pricing Page.