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Machine learning

Machine Learning is basically making a computer perform a work without unequivocally programming it. It provides advanced level knowledge on Machine Learning applications and counts. It will give you hands-on experience in various, incredibly searched for machine learning skills in both controlled and unsupervised learning.

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Machine learning

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  1. Machine learning Let’s Get Started!

  2. Description Machine Learning is basically making a computer perform a work without unequivocally programming it. It provides advanced level knowledge on Machine Learning applications and counts. It will give you hands-on experience in various, incredibly searched for machine learning skills in both controlled and unsupervised learning.

  3. Objectives • Categorize the types of learning including supervised and unsupervised • Perform supervised learning methods: linear and logistic regression • Recognize classification data and models • Recognize the several applications of machine learning systems • Use unsupervised learning algorithms including clustering, deep learning, and recommendation systems • Use machine learning with Spark

  4. Benefits • Facilitates Accurate Medical Predictions and Diagnoses • Simplifies Time-Intensive Documentation in Data Entry • Improves Precision of Financial Rules and Models • Easy Spam Detection • Increases the Efficiency of Predictive Maintenance in the Manufacturing Industry • Better Customer Segmentation and Accurate Lifetime Value Prediction • Recommending the Right Product

  5. Prerequisite This training program will be performed in python / R hence we have an introduction to these languages in the program itself.

  6. This course is appropriate for: • Working professionals who want to work in machine learning • Software professionals looking for a career switch into the field of analytics • Data Science professionals who already have experience in R or Python • 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 clients • Professionals working in ecommerce, search, and other online consumer based organizations

  7. Course Topics • Introduction to Machine Learning • Walking with Python or R • Machine Learning Techniques 13:47 • Supervised Learning 15:05 • Supervised Learning - Regression 15:05 • Supervised Learning - Classification • Unsupervised Learning • Unsupervised Learning - Clustering • Unsupervised Learning - Recommendation • Unsupervised Learning – Deep Learning • Spark Core and MLLib

  8. Thank You!

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