Machine Learning Python Course
iFlame Institute’s Machine Learning course with python in Ahmedabad helps you gain expertise in a types of machine learning algorithms such as classification, regression, clustering, decision trees and Association Learning. This Machine Learning course using Python Training exposes you to concepts of linear regression, logistic regression, decision tree, random forest, Nativ Bayes, least square, principal component analysis, principal component regression and real world machine learning training. Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This Machine Learning course with Python will give you all the tools you need to get started with supervised and unsupervised learning.
What is Machine Learning?
Machine learning is a category of algorithm that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in the applications of email filtering, detection of network intruders, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. (Content source by Wikipedia https://en.wikipedia.org/wiki/Machine_learning)
WHAT YOU WILL LEARN
- Build features that meet analysis needs
- Create and evaluate data clusters
- Describe how machine learning is different than descriptive statistics
- Explain different approaches for creating predictive models
- The Most common Supervised vs Unsupervised Machine Learning Algorithms
- How Statistical Modeling relates to Machine Learning, and how to do a comparison of each.
- Different ways machine learning affects society
Who can take this course?
- Anyone willing and interested to learn machine learning algorithm with Python.
- Anyone who has a deep interest in the practical application of machine learning to real world problems.
- Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms.
- Anyone who wants to apply machine learning to their domain.
Machine Learning Projects
The best way to learn machine learning is to apply it yourself. The machine learning projects included in the course will help you to develop machine learning skills while giving you an opportunity to discover interesting data-related problems. in addition, these machine learning projects can be built-in into your portfolio, making it easier to land a machine learning job.
In the iFlame Institute 1-1 mentor track, you will be assigned an Industry expert mentor, who will manage your Machine Learning project and guide you throughout the duration of the project. You will get 2 hour of each session with the expert.
This machine learning course will expose you to various Classification, Association, Clustering and Regression data-related problems by providing hands-on experience working with any of the datasets listed below-
- 1. Iris Dataset Prediction Project
- 2. Board Game Review Prediction Project
- 3. Credit Card Fraud Detection Project
- 4. Object Recognition Project