Complete Introduction to Data Science and Machine Learning from Basic to Advanced.
What you will learn
Students will have develop understanding of libraries used for Data Analysis like Pandas and Numpy.
Learn to create impactful visualizations using Matplotlib and Seaborn. By creating these visualizations you will be able to derive better conclusions from data.
After this course you will learn to build complete Data Science Pipeline from Data preparation to building the best Machine Learning Model.
The course contains practical section after every new concept discussed and the course also has two projects at the end.
Description
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Welcome and Course Overview
Welcome
Course Overview
Numpy
Numpy Introduction and Installation
Creating Arrays in Numpy
Array Shape and Reshape
Array Indexing
Array Iterating
Array Slicing
Searching and Sorting
Pandas
Pandas Introduction and Installation
Pandas Series
Pandas DataFrame
Pandas ReadCSV
Pandas Analyzing DataFrames
Data Visualization
Matplotlib Introduction
Different types of plots in Matplotlib
Seaborn
Data Preparation
Handling Missing Values
Feature Encoding
Feature Scaling
Machine Learning
Machine Learning Introduction
Supervised Machine Learning
Unsupervised Machine Learning
Train Test Split
Regression Analysis
Linear Regression
Logistic Regression
KNN
SVM
Decision Tree
Random Forest
K Means Clustering
GridSearch CV
Machine Learning Pipeline
Machine Learning Pipeline
Projects
Diabetes Prediction
Insurance Cost Prediction
