Machine learning can be utilized in inter-domain discipline. Each type of business wants to apply in their own work. Now the question is what is ML and Why is important for every business?
It is an automated method that learns from previous experiences or data and tries to predict the future outcome. It is a sub-extension or branch of artificial intelligence.
Machine learning in cross-domain has proved that it worked well and helps a lot in the better decision-making process. Like Emails or Ads Spam Detection, Progress in Financial Procedures, Precise Medical Analyses, and Product Marketing, sales.
So as a beginner, you have to start learning this skill for improvement in your domain and research growth. For learning purposes, I made a small machine learning workshop to increase your knowledge as well as your interest. If you are a student and want to learn these skills, it’s the perfect time to review the things, Start learning from today. There are tons of research projects all around the world you can deploy. Here is some Latest Topics for Research in Technology and Computer Science
The Machine Learning with Python course introduces the essentials concepts of machine learning using Python. You’ll determine the differences between supervised and unsupervised learning and how statistical modeling relates to machine learning, we’ll look at a variety of common techniques, including classification, regression, and clustering. Also, jump to Deep Learning and build First Artificial Neural Network Model. The major outline of this workshop includes:
- Machine Learning Introduction
- Python Programming Basics.
- Pandas Library for Data Preprocessing.
- Linear Regression- Construction of the First Model.
- NLP Classification (Spam Filter Model Using SVM).
- Introduction to Deep Learning & Artificial Neural Networks.
- Construction and understanding the First Artificial Neural Network.
All source code is uploaded on GitHub, you can access and exploit your skills and knowledge.
GitHub Repository for Machine Learning Workshop
Thanks.