Learn complete Python and Machine learning, build projects and start your Machine Learning Career
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The whole world has been in constant change since the release of computers and the internet! They used to be an extra hand to the capabilities of the human mind since the last couple of decades.
Recently, with the advances in the power of computers and ease of access to the large amount of information, it has been made possible to run special algorithms on these tufts of data!
How Machine learning works – With the availability of a tremendous amount of DATA and the ease in accessing them, it is possible to make the computers learn to take decisions. Once we have enough data, ML algorithms are employed based on this data and we get nearly accurate results through prediction. As more data is accumulated, the accuracy improves. Accurate algorithms are then created and data-driven predictions are obtained. You will see in details how this actually happens during this course.
This course gives you COMPLETE know how of Python & Machine Learning, and hence making you are confident enough to launch your career in the world of ML and AI.
For any doubts or concerns please contact +91-9266677335.
Once you complete the course and all the assignments you will be granted a soft and hard copy of the completion certificate.
If you are working professional and wants to enhance your skills, we will provide you an experience letter once you complete the course and have worked on the machine learning projects
Details related to Guaranteed Internship:
i) Why? - We believe acquiring a new skill without working on an actual project is wasteful spending of your time and resources. For your holistic learning experience, both course and internship should be combined.
ii) Who? - An Internship is guaranteed by Eckovation to all Eckovation Alumni - those who complete at least a course with us.
iii) Where? - The Internship will be either with Eckovation or one of our partner organizations. You will be able to access internship.eckovation.com once you register for a course with us. Our Internship Portal will feature profiles of our alumni and also list internship opportunities by various organizations where alumni can apply.
iv) How many? - The internship will be related to the skill(s) which you've acquired from Eckovation platform. In case of multiple skills, multiple internship opportunities may be provided.
v) Nature of internship? - The internships will be virtual in nature, i.e., you will be able to work on the internship project from home.
vi) When? - The Internship will start only after your course completion in either Summer/December Vacation depending on which comes first. In-semester internships can also be considered on case-by-case basis.
vii) Certificate - A separate internship certificate will be provided at the end of the internship period.
All the concepts required for Machine Learning
What is Supervised Learning?
What is Unsupervised Learning?
Simple Linear Regression
Multiple Linear Regression
Assumptions of Linear Regression
Applications of Linear Regression
Difference b/w linear and logistics regression
Difference b/w Multiple Regression and Multivariate Regression
Step wise Python Implementation
Tuning Parameters: Kernels, Regularization, Gamma, Margin
When to use PCA
Working of PCA
Need for LDA
Representation of Model
How to make predictions from a learned LDA
Single-link and complete-link clustering
Time complexity of HAC
Group-average Agglomerative clustering
Optimality of HAC
What is Naive Bayes algorithm?
How Naive Bayes Algorithms works?
What are the Pros and Cons of using Naive Bayes?
Applications of Naive Bayes Algorithm
Steps to build a basic Naive Bayes Model in Python
Tips to improve the power of Naive Bayes Model
Neural network Introduction
Build your industry grade, resume ready project
A BITS Pilani graudate, with experience of over 8 years.
Over last couple of years, he has been associated with the top companies like Oracle, and eBay.
He is a proficient software architect, with deep experience in building highly scalable systems distributed online systems.
He has in-depth working knowledge of technologies like Machine Learning system, MEAN stack and many more.