What you would learn in Feature Engineering For Data Science course?
Are you interested in data analytics, Business Analytics, Data Science, or Machine Learning?
Do you wish to learn advanced to beginner level Engineering?
Are you interested in knowing the best methods to cleanse data and extract valuable insight from it?
Are you looking to reduce time and speedily perform exploratory data analysis(EDA)?
If so, this course is designed suitable for you!!
As per Forbes: "60% of the Data Scientist's or Data Analyst's day is spent sorting out and organizing their data ..."
In this class, you won't just learn about the strategies used by industry professionals, but I will also show them to help you understand them better.
The course was designed to be practical and thoughtfully developed by experts in the field to simulate the real-world situation of dealing with chaotic data.
This course will assist you in mastering complicated Data Analytic techniques and concepts for better understanding and manipulating data.
We'll guide you step-by-step through each subject by explaining each line of code to aid in your comprehension.
The course is structured in the following manner:
Introduction to Basic Concepts
How to Properly Deal with Python Data Types
How To Correctly Deal With Time and Date in Python
How to Deal With Values That Aren't There
How to Manage Outliers
How to Manage Data Imbalance
How to Handle Data Leakage
How to deal with Categorical Values
Beginning to Advanced Data Visualization
Different Feature Engineering Techniques include:
Features Encoding
Features Scaling
Features Transformation
Feature Normalization
Automated feature EDA Tools
pandas-profiling
Dora
Autoviz
Sweetviz
Automation of Feature Engineering
RFECV
FeaturesTools
FeatureSelector
Autofeat
This course will aid beginners, intermediate data analysts, students business analysts, data science, and machine learning enthusiasts grasp the basics of using data within the context of real life.
Course Content:
- Master Exploratory Data Analysis (EDA) Utilizing Python
- Master the Art of Dealing With the flurry of data
- Learn to deal with Outliers
- Learn how to deal with Incomplete Data
- Master the Techniques to Deal With Data Leakage
- Learn to deal with poor Machine learning algorithms & Models
- Be aware of how to handle complex data Cleaning Problems in Python
- Learn about automated tools and Libraries to help professionals clean and maintain data and Analysis
- Learn the skills required to Make It To The Top 10% of Data Science and Analytics Science
- Learn the Best Methods to Make Your Data Ready To Create Machine Learning Models
- Learn Different Methods of Dealing with raw Data
- Do Industry Level Data Engineering
- Learn to Feature Encode Features
- Learn Feature Normalization
- Anyone interested in learning how to handle complex machine learning issues like imbalance data, leakage of data, essential to advanced feature Engineering, and more.
- One-Hot Encoding
- Label Encoding
- Curse Of Dimensionality
- A Feature Harsher(The Hashing Technique)
- Scaling of Feature
- Standardization
- Robust Scaler
- Transformation of Feature
- Polynomial Transformation
- Tool Features
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