Building a Machine Learning App Interface

Machine learning is basically a way that our programs and applications can learn from different data that has been passed into our application to make 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 simple to build a CNN. This is a free online course that introduces you to Keras and you will learn the difference between TensorFlow and Keras. A dataset in machine learning is 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 a CNN works and how to classify images.

Next, you will learn how to run values through convolutional layers, and all the cool processing you need to do. The material describes how to build your CNN 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 Core ML. It explains the process of importing Core ML to a project in order to use it. This course teaches you how to perform OCR (optical character recognition) handwriting recognition using OpenCV, Keras, and TensorFlow. You will understand the process involved in making a prediction using Core ML 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, you are going to learn everything you need to know to start building more intelligent apps and your own machine learning models. Core ML is the foundation for domain-specific frameworks and functionality. It supports Vision for analyzing images, and 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 use it properly. It gives you hands-on knowledge on how to correctly integrate machine learning into iOS apps. You will be guided on how to make a custom UI (user interface) collection view flow layout. This course will be of benefit to website and application developers, and digital or data analysts with basic knowledge of the Python environment. This course has not been updated with the use of Generative AI models, like ChatGPT.