Machine Learning with R & Tensor flo

Service Description

This course outlines the collation of information and Data using algorithms. Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Many industries working with large amounts of data have recognized the value of machine learning technology. By gleaning insights from this data, organizations are able to work more efficiently or gain an advantage over competitors. To get the most value from machine learning this course on Machine Learning will teach you most of the key machine learning using R. R is particularly suited to learning machine learning due to user friendliness and the powerful R Studio IDE you will then go onto to learn through practical projects. During the second part of this training programme you will investigate Tensor flow which is the most popular and powerful open source machine learning/deep learning framework developed by Google for everyone. Tensor flow has many powerful Machine Learning API such as Neural Network, Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Word Embedding, Seq2Seq, Generative Adversarial Networks (GAN), Reinforcement Learning, and Meta Learning. Through project and practical workshops you will be guided through a series of scenarios that will increase your understanding of this subject area. Course Highlights • What is machine learning • Supervised Learning Models • Unsupervised Learning Models • Neural Network • Basic Tensor flow 2 operations • Neural Network for Regression • Neural Network for Classification • Convolutional Neural Network for Vision • Recurrent Neural Network for Sequential Data • Transfer Learning • Tensor flow Hub