Machine Learning Data Science Training Jalandhar
What’s the focus of this course?
What are the course objectives?
- Classify the types of learning including supervised and unsupervised
- Identify the various applications of machine learning algorithms
- Perform supervised learning techniques: linear and logistic regression
- Understand classification data and models
- Use unsupervised learning algorithms including deep learning, clustering, and recommendation systems
- Use machine learning with Spark
Who should take this course?
- Analytics professionals who want to work in machine learning or artificial intelligence
- Data Science professionals who already have experience in R or Python
- Professionals working in eCommerce, search, and other online consumer based organizations
- Software professionals looking for a career switch into the field of analytics
- Graduates looking to build a career in Data Science and machine learning
- Experienced professionals who would like to harness machine learning in their fields to get more insight about customers
What projects will I complete as part of the course?
For this project, you’ll receive provide data about movies and users which will be used to train the model and generate recommendations for users about which movies they would like to watch, using the collaborative filtering technique.Project 2: Predict Loan Defaults
The data set for this project contains information on customers who received a Home Equity Line of Credit. The target variable is a flag. If the value is a “1” then the person defaulted on the loan. If the value is a “0” then the person repaid the loan. You’ll use the training data to develop a model to predict whether a customer will default on a loan, using the logistic regression technique.Submit one of the projects and on successful completion participant will receive an experience certificate.
Lesson 1: Introduction to Machine Learning
Lesson 2: Walking with Python or R
Lesson 3: Machine Learning Techniques
Lesson 4: Supervised Learning
Lesson 5: Supervised Learning – Regression
Lesson 6: Supervised Learning – Classification
Lesson 7: Unsupervised Learning
Lesson 8: Unsupervised Learning – Clustering
Lesson 9: Unsupervised Learning – Recommendation
Lesson 10: Unsupervised Learning – Deep Learning
Lesson 11: Spark Core and MLLib