Machine Learning- From Basics To Advanced. A beginners guide to learn Machine Learning (including Hands-on projects – From Basic to Advance Level)
Machine Learning- From Basics To Advanced
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.
Requirements
- Basic knowledge of scripting and programming
- Basic knowledge of python programming
Description
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
Machine Learning- From Basics To Advanced
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.
Git & GitHub A Practical Course: Beginner To Advanced Level
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
Machine Learning- From Basics to Advanced Download Link
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