Machine Learning & Data Science : Python Practical Hands-on

Machine Learning & Data Science : Python Practical Hands-on - Code, Develop, Validate & Deploy Machine Learning Models. Become a Champion with Machine Learning Algorithms.

New
Created by Abilash Nair
English [Auto]

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What you'll learn

Machine Learning Algorithms such as Supervised & Unsupervised algorithms
It will provide you with ability to execute Regression and Classification Algorithms
Create Machine Learning Models - Practical Sessions
KNN & K- Means Algorithm based model creation and validation accuracy determination
Cross Validation & Random Sampling
Data Processing with Pandas & Python
Feature Engineering & Data Pre-Processing
Working with Multiple Data Sets and Algorithm building in Kaggle Cloud.

Description

Interested in the field of Machine Learning? Then this course is for you!

Designed & Crafted by AI Solution Expert with 15 + years of relevant and hands on experience into Training , Coaching and Development.

Complete Hands-on AI Model Development with Python.

Course Contents are:

Fundamentals of Machine Learning

Machine learning project Life Cycle

Supervised & Unsupervised Learning

Data Pre-Processing

Algorithm Selection

Data Sampling and Cross Validation

Feature Engineering

Model Training and Validation

K -Nearest Neighbor Algorithm

K- Means Algorithm

Accuracy Determination

Visualization using Seaborn

You will be trained to develop various algorithms for supervised & unsupervised methods such as KNN , K-Means , Random Forest, XGBoost model development.

Understanding the fundamentals and core concepts of machine learning model building process with validation and accuracy metric calculation. Determining the optimum model and algorithm.

Cross validation and sampling methods would be understood.

Data processing concepts with practical guidance and code examples provided through the course.

Feature Engineering as critical machine learning process would be explained in easy to understand and yet effective manner.

We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

Who this course is for: