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by Super Admin
Estimated Time
On demand video
Enrolled By
Students & professionals
Total
Resources
Full
Access
Feature Scaling
Data Cleaning
Creating A Data Science Resume
Data Science Cover Letter
How to Contact Recruiters
Getting Started with Freelancing
Top Freelance Websites
Personal Branding
Networking
Importance of a Website
PCA Section Overview
What is PCA?
PCA Drawbacks
PCA Algorithm Steps (Mathematics)
Covariance Matrix vs SVD
PCA - Main Applications
PCA - Image Compression
PCA Data Preprocessing
PCA - Biplot and the Screen Plot
PCA - Feature Scaling and Screen Plot
PCA - Supervised vs Unsupervised
PCA - Visualization
Unsupervised Machine Learning Intro
Unsupervised Machine Learning Continued
Data Standardization
SVM Outline
SVM intuition
Hard vs Soft Margins
C hyper-parameter
Kernel Trick
Kernel Types
SVM with Linear Dataset (Iris)
SVM with Non-linear Dataset
SVM with Regression
[Project] Voice Gender Recognition using SVM
Ensemble Learning Section Overview
What is Ensemble Learning?
What is Bootstrap Sampling?
What is Bagging?
Out-of-Bag Error (OOB Error)
Implementing Random Forests from scratch Part 1
Implementing Random Forests from scratch Part 2
Compare with sklearn implementation
Random Forests Hyper-Parameters
Random Forests Pros and Cons
What is Boosting?
AdaBoost Part 1
AdaBoost Part 2
Decision Trees Section Overview
EDA on Adult Dataset
What is Entropy and Information Gain?
The Decision Tree ID3 algorithm from scratch Part 1
The Decision Tree ID3 algorithm from scratch Part 2
The Decision Tree ID3 algorithm from scratch Part 3
ID3 - Putting Everything Together
Evaluating our ID3 implementation
Compare with Sklearn implementation
Visualizing the tree
Plot the Important Features
Decision Trees Hyper-parameters
Pruning
[Optional] Gain Ration
Decision Trees Pros and Cons
Project] Predict whether income exceeds $50K/yr - Overview
KNN Overview
Parametic vs Non-Parametic Models
EDA on Iris Dataset
KNN - Intuition
Implement the KNN algorithm from scratch
Compare the Reuslt with Sklearn Library
Hyperparameter tuning using the cross-validation
The decision boundary visualization
Manhattan vs Euclidean Distance
Feature scaling in KNN
Curse of dimensionality
KNN use cases
KNN pros and cons
Linear Regression Intro
Gradient Descent
Linear Regression + Correlation Methods
Linear Regression Implemenation
Logistic Regression
Feature Engineering
Who is this course for?
Data Science + Machine Learning Marketplace
Data Science Job Opportunities
Data Science Job Roles
What is a Data Scientist?
How To Get a Data Science Job
Data Science Projects Overview
Exploratory Data Analysis
Intro to Machine Learning
Data Visualization Overview
Different Data Visualization Libraries in Python
Python Data Visualization Implementation
Intro To Pandas
Intro To Pandas Continued
Intro NumPy Array Data Types
NumPy Arrays
NumPy Arrays Basics
NumPy Array Indexing
NumPy Array Computations
Broadcasting
What Exactly is Probability?
Expected Values
Relative Frequency
Hypothesis Testing Overview
Intro to Statistics
Descriptive Statistics
Measure of Variability
Measure of Variability Continued
Measures of Variable Relationship
Inferential Statistics
Measure of Asymmetry
Sampling Distribution
What is Programming?
Why Python for Data Science?
What is Jupyter?
What is Google Colab?
Jupyter Notebook
Python Variables, Booleans
Getting Started with Google Colab
Python Operators
Python Numbers and Booleans
Python Strings
Python Conditional Statements
Python For Loops and While Loops
Python Lists
More about Lists
Python Tuples
Python Dictionaries
Python Sets
Compound Data Types and When to use each one?
Python Functions
Object-Oriented Programming in Python
Why We Use Python
What is Data Science?
What is Machine Learning?
Machine Learning Concepts and Algorithms
What is Deep Learning?
Machine Learning vs Deep Learning
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