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A complete Guide to Machine Learning by Systango

Machine Learning is one of those disruptive technologies that can automatically learn and improve from experience without being explicitly programmed. Learn from tech experts at Systango as to how to use machine learning in your platform for better user experience and performance.
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  • 1. fgjghjghj fhfdhj A Complete Guide to Machine Learning
  • 2. Contents ● What is Machine Learning ● Automation vs ML vs AI ● Why Machine Learning ● Need for Machine Learning ● Machine Learning Techniques ● Live Tutorial (Supervised Learning) ○ Datasets ○ Algorithms: KNN Classification ○ Code Explanation
  • 3. What is Machine Learning? Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. SOURCE
  • 4. Automation Automation is making a machine or software do things automatically — without human intervention. Automation vs ML vs AI Artificial Intelligence AI is making machines or software to mimic & supersede human behaviour and intelligence. Machine Learning ML is making machines & software to mimic intelligence through ability to learn & improve from experience.
  • 5. Why Machine Learning ● Problem Solving ● Decision-Making ● Recognition ● Translation Abilities ● Acute Perception
  • 6. What is needed for ML? Processing Power
  • 7. What is needed for ML? Models (Algorithms)
  • 8. What is needed for ML? Data
  • 9. Machine Learning Techniques MACHINE LEARNING UNSUPERVISEDSUPERVISED CLASSIFICATION REGRESSION CLUSTERING ASSOCIATION
  • 10. Classification Classification is used where the prediction or the answer has to be from a selected set of “classes” ● Whether india will win or lose a cricket match? ● Whether an email is spam or genuine? ● Whether this article is based on technology , sports or entertainment?
  • 11. Regression Regression is used where the prediction needs continuous response ● Weather Forecast ● Stock Market Trends & Performance ● Sales Forecasting
  • 12. Clustering Clustering is about grouping data items into subsets that have some measure of similarity based on characteristic values. ● Group Customers by behavior purchase ● Image Segmentation ● Anomaly Detection
  • 13. Association Association is about discovering some interesting relationships between variables in large databases. ● People who tend to buy new house also tend to buy new furniture ● Friend Suggestions ● Netflix Movie Suggestions
  • 14. K Nearest Neighbour Algorithm KNN Classification: ● This algorithm is used for classification ● It stores all available cases from training data and classifies new cases based on a similarity measure ● These similarity measures could be Distance functions or cosine similarity.
  • 15. Experience of the Candidate Numberofcorrectanswers
  • 16. DO YOU HAVE ANY QUESTIONS? www.systango.com hello@systango.com UK: +44 1253 547777 Want to know more about ML? Go to Systango Now.
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