Introduction to Machine Learning Algorithms and their Implementation in Python in Bangalore
5.0 /5- Offered bySkill Lync
Introduction to Machine Learning Algorithms and their Implementation in Python in Bangalore at Skill Lync Overview
Duration | 3 months |
Total fee | ₹7,000 |
Mode of learning | Online |
Credential | Certificate |
Introduction to Machine Learning Algorithms and their Implementation in Python in Bangalore at Skill Lync Highlights
- Industry-oriented curriculum.
- Hands-on experience in solving industry projects.
- Email and forum support from the technical support team to clear your doubts.
- A certificate of completion for all participants and a merit certificate for the top 5% of the scorers.
Introduction to Machine Learning Algorithms and their Implementation in Python in Bangalore at Skill Lync Course details
- Student will learn about the basics of data science, and the implementation of Python to develop machine learning algorithms.
- Throughout this course, student will have numerous opportunities to exercise their understanding by completing challenges and projects that require extensive analysis of data sets.
- Python is a robust programming language used in the development of machine learning algorithms
- This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects
- This course will give student a solid understanding of the essential Python libraries, evaluation metrics, univariate and multivariate linear regression, K-Mean clustering, hierarchical clustering, and neural networks.
Introduction to Machine Learning Algorithms and their Implementation in Python in Bangalore at Skill Lync Curriculum
Week 1 - Introduction to Data Science and Programming Languages (Tools) for Data Science
Data Science and Big Data: Introduction
Importance of Data Science and Big Data
Introduction to Different Programming Languages (Tools) for Data Science
Week 2 - Basics of Programming
Variables
Operators
Data Types
Data Structures
Control Structures in Python
Function File in Python
Week 3 - Essential Python Libraries
NumPy
SciPy
Pandas
Matplotlib
Seaborn
Week 4 - Introduction to Machine Learning Cross-Validation, Bias-Variance Tradeoff
Basics of Machine Learning
Classification
Fitting of Model with Cross-Validation
Bias Variance Tradeoff
Week 5 - Evaluation Metrics
Evaluation Metrics for Model Validation
Week 6 - Importing Data and Hands-On Imported Data
Exploratory Data Analysis (EDA)
Correlation
Feature Extraction
Hyper Parameters
Week 7 - Univariate and Multivariate Linear Regression
Univariate Linear Regression
Multivariate Linear Regression
Implementation in Python
Week 8 - Principal Component Analysis
Eigen Values
Eigen Vectors
Singular Value Decomposition
Principal Component Analysis (PCA)
Week 9 - Logistic Regression and k-nearest Neighbor
Explanation and Implementation of Logistic Regression and k-nearest Neighbor in Python
Week 10 - Decision Tree and Random Forest
Explanation and Implementation in Python
Decision Tree
Random Forest
Week 11 - K-Mean and Hierarchical Clustering
K-Mean
Hierarchical Clustering
Week 12 - Neural Networks
Logistic Regression with Neural Network Mindset
Introduction to Machine Learning Algorithms and their Implementation in Python in Bangalore at Skill Lync Entry Requirements
- Students with a background in electrical engineering can apply for this machine learning course.
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