Machine Learning Course in Jaipur


Build Intelligent Applications


Course Name – Machine Learning Course                               

Duration – 1.5 Months


About Machine Learning course: Machine Learning Course is that the science of getting computers to act without being explicitly programmed. Within the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you simply probably use it dozens of times each day without knowing it. Many researchers also think it’s the simplest thanks to make progress towards human-level AI. During this class, you’ll study the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll study not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you’ll study a number of Silicon Valley’s best practices in innovation because it pertains to machine learning and AI.


This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition.


Topics include:


(i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).


(ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).


(iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).


The course also will draw from numerous case studies and applications, in order that you’ll also find out how to use learning algorithms to put together smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.




Basic programming skills (in Python), algorithm design, basics of probability & statistics


Detailed Contents of Machine Learning Course :


  • Machine learning algorithms

  • Techniques of Machine Learning

  • Applications of Machine Learning

  • Review of algebra 

  • Data Reprocessing

  • Supervised learning algorithms

  • Linear Regression with single Variable

  • Linear Regression with Multiple Variables

  • Logistic Regression & Random Forest

  • Decision Tree Regression

  • Classification using KNN

  • Classification using GINI

  • Classification using SVM(support vector machine)

  • Neural Networks: Representation

  • Neural Networks: Learning for regression and classification

  • Unsupervised learning – Clustering

  • Mining of knowledge using LSI

  • Large Scale Machine Learning


Machine learning may be a branch of science that deals with programming the systems in such a way that they automatically learn and improve with experience. Here, learning means recognizing and understanding the input file and making wise decisions supported the supplied data.


It is very difficult to cater to all or any of the choices supported all possible inputs. To tackle this problem, algorithms are developed. These algorithms build knowledge from specific data and past experience with the principles of statistics, probability theory, logic, combinatorial optimization, search, reinforcement learning, and control theory.