Machine Learning- From Basics to Advanced

Summary, Description

If you want to start your career in Machine Learning, this is your course.

This is a course built such that all the principles of machine learning can be taught from basic to advanced stages.

As given below, this course has 5 parts:

Data Wrangling & Introduction of machine learning

Deep Learning Linear Structures, Trees & Preprocessing

Model Evaluation, Selection of Features & Pipelining in machine learning

Bayes, Closest Neighbours & Machine learning clustering

In machine learning, SVM, Anomalies, Imbalanced Classes, Ensemble Methods

Who would teach you in this class?

I am a technical educator and consultant for C, C++, Python, Java, Scala, Big Data Technology – PySpark, Spark using Scala Machine Learning & Deep Learning- sci-kit-learn, TensorFlow, TFLearn, Keras, h2o and distributed to companies such as GE, SCIO Health Analytics, Impetus, IBM Bangalore & Hyderabad, Redbus, Schnider, JP Morgan – Singapore & Hong Kong, CISCO, Flipkart, MindTree, DataGenic I have expressed my understanding that will guide you to consider the holistic approach to ML.

Machine learning is, alongside AI, the fuel we need to control robots. With Machine Learning, to respond to new environments and activities to get stuff done quickly and effectively, we can power programmes that can be easily upgraded and changed.

Here are a few arguments for you to try a Machine Learning career:
1) Machine learning is a skill of the future; the sector faces a lack of expertise amid the rapid increase of machine learning. You can have a stable future in a technology that is on the rise if you can satisfy the demands of big corporations by acquiring experience in Machine Learning.
2) Work on genuine problems

Course Link