Machine Learning and Data Mining with Weka - For Beginners
What you'll learn
- Download and Install Weka
- Practical use of Machine Learning
- Data sources and file formats
- Preprocess, Classifies, Filters & Datasets
- Practical use of Data Mining
- Experimenting & Comparing Algorithms
- A computer and internet connection.
This introductory course will help make your machine learning journey easy and pleasant , you will be learning by using the powerful Weka open source machine learning software, developed in New Zealand by the University of Waikato.
You will learn complex algorithm behaviors in a straightforward and uncomplicated manner. By exploiting Weka's advanced facilities to conduct machine learning experiments, in order to understand algorithms, classifiers and functions such as ( Naive Bayes, Neural Network, J48, OneR, ZeroR, KNN, linear regression & SMO).
Image, text & document classification & Data Visualization
How to convert bulk text&HTML files into a single ARFF file using one single command line
Difference between Supervised & Unsupervised Machine Learning methods
Practical tests, quizzes and challenges to reinforce understanding
Weka's intuitive, the Graphical User Interface will take you from zero to hero. You will be learning by comparing different algorithms, checking how well the machine learning algorithm performs till you build your next predicative machine learning model.
Who this course is for:
- Anyone curious about machine learning without programming.
- Anyone who wants to explore data engineering and data science.
ICT QA&Test Consultant & MBCS - (BSc (Honours) Open) - (Diploma in Computing). (ISO 9000/1 - FDA ISTQB & Agile Certified) - (Oracle & HP-UNIX Admin Certified).
With 30 years’ experience and know-how in ICT working for large organizations and in diverse industries such as Teaching, Software houses, Telecommunications, Banking, Health Care and Pharmaceuticals.
I hold a BSc Honors degree, Diploma in Computing & BTEC-HNC from The Open University Milton Keynes and Norwich City College – UK England. I'm a professional member of the British Computer Society (MBCS) and a member of IBM Data Science Community.
I'm tech enthusiast and a machine learning practitioner who loves software engineering, RDBM's, Android mobile development, web site development and automation.
Major Subjects : Computer Science, Software engineering, databases, data Models, computer architecture, digital electronics, programming, mathematics , statistics, quantitative methods & (Artificial intelligence for technology OCR-Neural Network).