Machine Learning Bootcamp in Python with 5 Capstone Projects
Learn how to use Machine Learning with Python. Build 5 Complete Machine Learning Real World Projects with Python.
What you’ll learn
-
Theory and practical implementation of linear regression using sklearn
-
Theory and practical implementation of logistic regression using sklearn
-
Feature selection using RFECV
-
Data transformation with linear and logistic regression.
-
Evaluation metrics to analyze the performance of models
-
Industry relevance of linear and logistic regression
-
Mathematics behind KNN, SVM and Naive Bayes algorithms
-
Implementation of KNN, SVM and Naive Bayes using sklearn
-
Attribute selection methods- Gini Index and Entropy
-
Mathematics behind Decision trees and random forest
-
Boosting algorithms:- Adaboost, Gradient Boosting and XgBoost
-
Different Algorithms for Clustering
-
Different methods to deal with imbalanced data
-
Correlation Filtering
-
Variance Filtering
-
PCA & LDA
-
Content and Collaborative based filtering
-
Singular Value Decomposition
-
Different algorithms used for Time Series forecasting
-
Case studies
Requirements
-
To make sense out of this course, you should be well aware of linear algebra, calculus, statistics, probability and python programming language.
Who this course is for:
- Anyone who want to start a career in Machine Learning.
- Students who have at least knowledge in linear algebra, calculus, statistics, probability and who want to start their journey in Machine Learning.
- Any people who want to level up their Machine Learning Knowledge.
- Software developers or programmers or Tech lover who want to change their career path to machine learning.
- Technologists who are curious about how Machine Learning works in the real world.
- Anyone who has already started their data science journey and now want to master in machine learning.
- If you have no prior coding or scripting experience, This course is completely for you. This Course also includes Python Fundamental for beginners.
![JavaScript Coding Interview Questions [with SOLUTIONS]](https://www.tutorialbar.com/wp-content/themes/rehub-theme/images/default/noimage_336_220.png)