explanation
Machine Learning in Python with 5 Machine Learning Projects is a Python machine learning training bootcamp where you will build 5 real-world machine learning projects using Python. This step-by-step course introduces you to the world of machine learning. Machine learning is the science of computer algorithms used to automate model analysis and is also a branch of artificial intelligence.
What you’ll learn about machine learning in Python with 5 machine learning projects:
- Theoretical discussion and practical implementation of linear regression using sklearn
- Theoretical discussion and practical implementation of logical regression using sklearn
- Characterization using RFECV
- Data transfer using linear and logistic regression
- Evaluation criteria for model performance analysis
- Industry relationships in linear and logistic regression
- Mathematical discussion of KNN, SVM and Naive Bayes algorithms
- Using KNN, SVM, and Naive Bayes using sklearn
- Feature Selection Methods – Gini Index and Entropy
- The Mathematics of Decision Trees and Random Forests
- Boosting algorithms using Adaboost, Gradient Boosting, and XgBoost
- Types of algorithms for classification
- Different ways to handle imbalanced data
- Specification of relationships and variables
- PCA and LDA
- Various algorithms used for time series forecasting
Course specifications
Publisher: Udemy
teacher: Academy with good data
Language:English
Education level: from basic to advanced
Number of courses: 381
Duration: 24 hours 11 minutes
2021/7 Course Topics:
Course Prerequisites:
To understand this course, you should be familiar with linear algebra, calculus, statistics, probability, and the Python programming language.
movie
Course introduction video:
installation manual
After extracting, watch with your favorite players.
English subtitles
Quality: 720p
Previous course title: Machine Learning in Python Bootcamp with 5 Capstone Projects
download link
File password: free download software
size
21.1GB