MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 12 lectures (1 hour, 48 mins) | Size: 1.04 GB
Machine Learning is getting increasingly famous for new aspirants to learn.
What you'll learn
Feature Eeering with Excel
Building Machine Learning models with Python
Getting started with their first Kaggle Competition
Learning to build and choose best Machine Learning Model
Requirements
Excel Functions - IF, Sumifs, Counta, Vlookup
Excel Pivot Tables
Excel Name Manager
Basic of Python for Machine Learning
Python Jupyter Notebooks
Description
I have seen many start this journey of never-ending learning start using Python or R to b their journey. Due to all coding and no visual cue's many often miss the joy of creating features and expenting with data using Excel.
I started my journey of Data Science with Excel, which helped me create a visual memory for creating features. My love for Data Science began with this simple yet powerful tool and a plethora of opportunities to solve new problems.
In this video series, I will extract features using the Titanic Data from Kaggle. Excel will be used to do missing value treatment, eeering new features, creating test and train datasets. Python is our choice of tool for modelling. Hopefully, as a bner, you will b to discover Data Science as I have.
Who this course is for:
Bner Data Science aspirants want to solve their first Kaggle Problem Statement
Data Science Students who want to learn how Feature Eeering happens visually
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