Getting Started with Machine Learning Algorithms
4.7 /5- Offered bySimplilearn
- Private Institute
- Estd. 2010
Getting Started with Machine Learning Algorithms at Simplilearn Overview
Duration | 6 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Getting Started with Machine Learning Algorithms at Simplilearn Highlights
- Earn a certificate and avail a 90 Days of access to this free course by Simplilearn
- Complete this course and develop a potential to earn $112K as average salary
Getting Started with Machine Learning Algorithms at Simplilearn Course details
- For Machine learning enthusiasts, Software engineers, Data scientists, Data analysts and Statisticians
- supervised learning algorithms
- unsupervised learning algorithms
- k-means clustering
- PCA
- Reinforcement learning
- Q-learning
- Linear regression
- Logistic Regression
- Decision tree
- Random forest
- This free course will help you learn machine learning algorithms in great depth
- By the end of this course, you will be trained in the skills essential for a skilled machine learning engineer
- Common careers for machine learning professionals include Machine learning engineer, Data scientist, Artificial Intelligence engineer and NLP scientist
Getting Started with Machine Learning Algorithms at Simplilearn Curriculum
Introduction
Introduction ML Algorithm
Lesson 01: Introduction to Machine Learning
Introduction to Machine Learning
Lesson 02: Supervised Learning Algorithms- Linear Regression
Supervised Learning Algorithms- Linear Regression
Lesson 03: Logistic Regression
Logistic Regression
Lesson 04:Decision Tree
Decision Tree
Lesson 05: Random Forest
Random Forest
Lesson 06: Support Vector Machine (SVM)
Support Vector Machine(SVM)
Lesson 07: K Nearest Neighbors (KNN)
K Nearest Neighbors(KNN)
Lesson 08: Unsupervised Learning Algorithms- K means Clustering
Unsupervised Learning Algorithms- K means Clustering
Lesson 09: Principal component analysis (PCA)
Principal component analysis(PCA)
Lesson 10: Reinforcement Learning
Reinforcement Learning
Lesson 11: Q Learning
Q Learning
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