Learn Machine Learning with Weka

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Price: 199.99$

Why learn Data Analysis and Data Science?According to SAS, the five reasons are1. Gain problem solving skills The ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life. 2. High demand Data Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase. 3. Analytics is everywhere Data is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It’s a hugely exciting time to start a career in analytics.4. It’s only becoming more important With the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities. 5. A range of related skills The great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths.  Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise. The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities. This is the bite-size course to learn Weka and Machine Learning. You will learn Machine Learning which is the Model and Evaluation of the CRISP Data Mining Process. You will learn Linear Regression, Kmeans Clustering, Agglomeration Clustering, KNN, Naive Bayes, and Neural Network in this course.  Content Getting Started Getting Started 2Data Mining Process Simple Linear Regression Regression in Weka KMeans Clustering KMeans Clustering in Weka Agglomeration Clustering Agglomeration Clustering in Weka Decision Tree: ID3 Algorithm Decision Tree in Weka KNN Classification KNN in Weka Naive Bayes Naive Bayes in Weka What Algorithm to use?Model Evaluation Weka Advanced Attribute Selection Weka Advanced Data Visualizations Weka Model Selection and Deployment