Machine Learning- From Basics to Advanced

A beginners guide to learn Machine Learning (including Hands-on projects - From Basic to Advance Level)

4.45 (2212 reviews)
Udemy
platform
English
language
Data Science
category
Machine Learning- From Basics to Advanced
297,915
students
7 hours
content
Apr 2020
last update
$39.99
regular price

What you will learn

Learn how to use NumPy, to do fast mathematical calculations in machine learning.

Learn what is Machine Learning and Data Wrangling in machine learning.

Learn how to use scikit-learn for data-preprocessing in machine learning.

Learn different model selection and feature selections techniques in machine learning.

Learn about cluster analysis and anomaly detection in machine learning.

Learn about SVMs for classification, regression and outliers detection in machine learning.

Description

If you are looking to start your career in Machine learning then this is the course for you.

This is a course designed in such a way that you will learn all the concepts of machine learning right from basic to advanced levels.

This course has 5 parts as given below:

  1. Introduction & Data Wrangling in machine learning

  2. Linear Models, Trees & Preprocessing in machine learning

  3. Model Evaluation, Feature Selection & Pipelining in machine learning

  4. Bayes, Nearest Neighbors & Clustering in machine learning

  5. SVM, Anomalies, Imbalanced Classes, Ensemble Methods in machine learning

For the code explained in each lecture, you can find a GitHub link in the resources section.


Who's teaching you in this course?

I am Professional Trainer and consultant for Languages C, C++, Python, Java, Scala, Big Data Technologies - PySpark, Spark using Scala Machine Learning & Deep Learning- sci-kit-learn, TensorFlow, TFLearn, Keras, h2o and delivered at corporates like GE, SCIO Health Analytics, Impetus, IBM Bangalore & Hyderabad, Redbus, Schnider, JP Morgan - Singapore & HongKong, CISCO, Flipkart, MindTree, DataGenic, CTS - Chennai, HappiestMinds, Mphasis, Hexaware, Kabbage. I have shared my knowledge that will guide you to understand the holistic approach towards ML.


Machine learning is the fuel we need to power robots, alongside AI. With Machine Learning, we can power programs that can be easily updated and modified to adapt to new environments and tasks to get things done quickly and efficiently.

Here are a few reasons for you to pursue a career in Machine Learning:
1) Machine learning is a skill of the future – Despite the exponential growth in Machine Learning, the field faces skill shortage. If you can meet the demands of large companies by gaining expertise in Machine Learning, you will have a secure career in a technology that is on the rise.
2) Work on real challenges – Businesses in this digital age face a lot of issues that Machine learning promises to solve. As a Machine Learning Engineer, you will work on real-life challenges and develop solutions that have a deep impact on how businesses and people thrive. Needless to say, a job that allows you to work and solve real-world struggles gives high satisfaction.
3) Learn and grow – Since Machine Learning is on the boom, by entering into the field early on, you can witness trends firsthand and keep on increasing your relevance in the marketplace, thus augmenting your value to your employer.
4) An exponential career graph – All said and done, Machine learning is still in its nascent stage. And as the technology matures and advances, you will have the experience and expertise to follow an upward career graph and approach your ideal employers.
5) Build a lucrative career– The average salary of a Machine Learning engineer is one of the top reasons why Machine Learning seems a lucrative career to a lot of us. Since the industry is on the rise, this figure can be expected to grow further as the years pass by.
6) Side-step into data science – Machine learning skills help you expand avenues in your career. Machine Learning skills can endow you with two hats- the other of a data scientist. Become a hot resource by gaining expertise in both fields simultaneously and embark on an exciting journey filled with challenges, opportunities, and knowledge.


Machine learning is happening right now. So, you want to have an early bird advantage of toying with solutions and technologies that support it. This way, when the time comes, you will find your skills in much higher demand and will be able to secure a career path that’s always on the rise.

Enroll Now!! See You in Class.


Happy learning
Team Edyoda

Content

Introduction to Machine Learning & Data Wrangling

Black Box Introduction to Machine Learning
Essential NumPy
Essential Pandas for Machine Learning

Linear Models, Trees & Preprocessing

Linear Models for Regression & Classification
Pre-Processing Techniques using scikit
Decision Trees

Model Evaluation, Feature Selection & Pipelining

Model Selection & Evaluation
Feature Selection Techniques
Composite Estimators using Pipelines & FeatureUnions

Bayes, Nearest Neighbours & Clustering

Naive Bayes
Nearest Neighbors
Cluster Analysis

SVM, Anomalies, Imbalanced Classes, Ensemble Methods

Anomaly Detection
Handling Imbalanced Classes
Support Vector Machine
Ensemble Methods

Reviews

Dayanand
November 15, 2023
The course began with a promising introduction to the basics, but it rapidly escalated into more complex topics without adequate transition or foundational buildup. This abrupt shift not only made it challenging to follow along but also left a significant gap in understanding for anyone not already familiar with the subject matter. The lectures were notably dry and unengaging. It appeared as though the instructor was merely reading from pre-written notes, lacking the enthusiasm and spontaneity that often make learning a dynamic and enjoyable experience. This approach significantly diminished the potential for interactive and engaging learning. The lectures were notably dry and unengaging. It appeared as though the instructor was merely reading from pre-written notes, lacking the enthusiasm and spontaneity that often make learning a dynamic and enjoyable experience. This approach significantly diminished the potential for interactive and engaging learning. The reliance on basic slides with minimal information was another drawback. The instructor often resorted to briefly commenting on each slide with only two or three lines of explanation, which is insufficient for understanding any topic in depth. This method left much to be desired in terms of content richness and educational value. The audio quality of the lectures was another significant issue. The lack of noise cancellation in the recording made it difficult to focus on the content, detracting from the overall learning experience. Investing in better audio equipment, such as a noise-cancellation microphone, is essential for delivering clear and professional lectures. Based on my experience, I cannot recommend this course to new learners or anyone looking for an in-depth and engaging educational journey. Those interested in this subject might be better served by exploring other courses that offer a more balanced approach to teaching, with better audio-visual quality and a more engaging instructional style.
Anagha
June 23, 2023
Its good but the teacher who teaches should explain things more clearly. Not everyone is going to understand what he teaches. He might be a very learned person but the teaching can be improved
M
June 22, 2023
Felt more like the teacher was revising it for themselves than teaching it to naive students, audio quality needs to improve. Unexpected outcome for a paid course
Deivisson
April 2, 2023
não estava claro pra mim quando comprei o curso que o professor seria não seria um falante nativo de inglês. o sotaque e a falta de legendas atrapalham
Tasman
February 27, 2023
He had just shown some slides and told two or three lines about each topic. Also the audio was awful. Please use a noise cancellation mic. And his presentation was not satisfactory.
Ramu
November 12, 2022
lecture was very quick since it is for beginner's needs to be little bit slower. For the work he has done the lecturer does not mention how to do practical work
Victor
August 24, 2022
Very educative and informative.Love to recommend it to all who want ML as a career Udemy is the place
Meher
June 26, 2022
Audio Quality is really bad... Not able to understand what he is saying... And skipping topics with just giving one liners about them
Alessandro
June 10, 2022
L'accento del prof e la mancanza di sottotitoli sono una combo perfetta per rendere poco chiari gli argomenti. Deluso
Sagar
June 7, 2022
Its not at all an intresting lecture, Looking at the way the teacher is taking lectures it looks like he is reading some pre-made notes.
Ryan
May 5, 2022
A lot of different models and data handling fitted in. I found the first parts and last parts to have great explanations along with it, but the middle sections were basically watching the lecturer quickly run through models without any deeper explanation.
Aniket
April 9, 2022
It was an amazing experience in learning this subject, the tutor was amazing and had good knowledge for the subject.
Zain
March 29, 2022
This man doesn't know how to explain, Audio is so bad and nothing is understanable. Not expected from paid course.
Saikat
January 12, 2022
Didn't expect this kind of teaching in a paid video. While teaching-"this is this and this is this" is not a kind of language I expected. I won't recommend this course to any new learner.
Avuyile
August 22, 2021
Wow, this course was super helpful in getting me started on my machine learning journey. It took too long for me to finish because I wanted to apply these concepts to my everyday data at work as a data analyst. Lastly, this did kind of take me back to my computational fluid dynamics days???. I hope the next person enjoys this course as much as I did or even more and improve on their skill set as well. Thank you!

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2932030
udemy ID
3/30/2020
course created date
4/13/2020
course indexed date
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