August 6, 2022August 6, 2022 Krita Infomatics TweetShareSharePin0 Shares Applied Statistics and Machine Learning Krita Infomatics Best Academic Writing Services Learning Outcomes:On completion of this module, learners will be able to:1. Understand the key concepts and techniques for pattern recognition on complex data sets..2. Decide when machine learning is an appropriate method to solve a problem.3. Understand and apply machine learning algorithms such as linear regression, SVM, kNN, RF, DT etc.4. Apply Machine Learning frameworks (e.g. scikit-learn, keras, tensorflow,…) to solve real-world problems.5. Understand and design approaches to process data (voice, image etc.) and extract certain patterns of interest from large datasets. Learning Activities:Each week will consist of a number of different activities:1. Introduction to concepts and theory using slides/ OneNote recorded in Panopto and live zoom lecturing.2. Implementation of theory using hands on examples in Python3. Q and A4. Tutorials Overview of Assessment: CA1 Assessment Title & Description :Task :MIMLOs being assessed :Individual/Group : CA 1Real world data processing and pattern recognition1,4,5Group CA2 Assessment Title & Description :Task :MIMLOs being assessed :Individual/Group : CA 2AI –based technology project using ML with Python2,3,4,5Individual TweetShareSharePin0 Shares