A beginners guide to learn Machine Learning (including Hands-on projects – From Basic to Advance Level)
What you’ll learn
- Learn how to use NumPy, to do fast mathematical calculations in machine learning.
- Learn what is Machine Learning and Data Wrangling in machine learning.
- Basic knowledge of scripting and programming
- Basic knowledge of python programming
This course has 5 parts as given below:
- Introduction & Data Wrangling in machine learning
- Linear Models, Trees & Preprocessing in machine learning
- Model Evaluation, Feature Selection & Pipelining in machine learning
- Bayes, Nearest Neighbors & Clustering in machine learning
- SVM, Anomalies, Imbalanced Classes, Ensemble Methods in machine learning
Who’s teaching you in this course?
I am Professional Trainer and consultant for Languages C, C++, Python, Java, Scala, Big Data Technologies – PySpark, Spark using Scala Machine Learning & Deep Learning- sci-kit-learn, TensorFlow, TFLearn, Keras, h2o and delivered at corporates like GE, SCIO Health Analytics, Impetus, IBM Bangalore & Hyderabad, Redbus, Schnider, JP Morgan – Singapore & HongKong, CISCO, Flipkart, MindTree, DataGenic, CTS – Chennai, HappiestMinds, Mphasis, Hexaware, Kabbage. I have shared my knowledge that will guide you to understand the holistic approach towards ML.
Machine learning is the fuel we need to power robots, alongside AI.
Who this course is for:
- Beginners who want to become a data scientist
- Software developers who want to learn machine learning from scratch
- Python developers who are interested to learn machine learning