Learn Machine Learning with Weka
Learn Machine Learning and Weka with this COurse
Description
Why learn Data Analysis and Data Science?
According to SAS, the five reasons are
1. 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 2
Data 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
What You Will Learn!
- Machine Learning using Weka Software
Who Should Attend!
- Beginner Data Analyst and Data Scientist interested to learn Machine Learning and Weka.