Clustering & Classification With Machine Learning In Python (Udemy.com)

( 99 Reviews )

Created by: Minerva Singh

Produced in 2021

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 94 / 100

Course Description

HERE IS WHY YOU SHOULD TAKE THIS COURSE: This course your complete guide to both supervised & unsupervised learning using Python. This means, this course covers all the main aspects of practical data science and if you take this course, you can do away with taking other courses or buying books on Python based data science. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal.. By becoming proficient in unsupervised & supervised learning in Python, you can give your company a competitive edge and boost your career to the next level. LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE: My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I also just recently finished a PhD at Cambridge University. I have several years of experience in analyzing real life data from different sources using data science techniques and producing publications for international peer reviewed journals. Over the course of my research I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic . This course will give you a robust grounding in the main aspects of machine learning- clustering & classification. Unlike other Python instructors, I dig deep into the machine learning features of Python and gives you a one-of-a-kind grounding in Python Data Science! You will go all the way from carrying out data reading & cleaning to machine learning to finally implementing simple deep learning based models using Python THE COURSE COMPOSES OF 7 SECTIONS TO HELP YOU MASTER PYTHON MACHINE LEARNING: - A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda- Getting started with Jupyter notebooks for implementing data science techniques in Python - Data Structures and Reading in Pandas, including CSV, Excel and HTML data- How to Pre-Process and - Wrangle- your Python data by removing NAs/No data, handling conditional data, grouping by attributes, etc. - Machine Learning, Supervised Learning, Unsupervised Learning in Python - Artificial neural networks (ANN) and Deep Learning. You-'ll even discover how to use artificial neural networks and deep learning structures for classification! With such a rigorous grounding in so many topics, you will be an unbeatable data scientist by the end of the course. NO PRIOR PYTHON OR STATISTICS OR MACHINE LEARNING KNOWLEDGE IS REQUIRED: You-'ll start by absorbing the most valuable Python Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python. My course will help you implement the methods using real data obtained from different sources. After taking this course, you-'ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python.. You-'ll even understand concepts like unsupervised learning, dimension reduction and supervised learning.. I will even introduce you to deep learning and neural networks using the powerful H2o framework! Most importantly, you will learn to implement these techniques practically using Python. You will have access to all the data and scripts used in this course. Remember, I am always around to support my students! JOIN MY COURSE NOW!Who this course is for:

Students Interested In Getting Started With Data Science Applications In The Python Environment
People Wanting To Master The Anaconda iPython Environment For Data Science & Scientific Computations
Students Wishing To Learn The Implementation Of Unsupervised Learning On Real Data Using Python
Students Wishing To Learn The Implementation Of Supervised Learning (Classification) On Real Data Using Python
Students Looking To Get Started With Artificial Neural Networks & Deep Learning

Time: 6h

Instructor Details

Minerva Singh

4.7 Rating
99 Reviews

Hello. I am a PhD graduate from Cambridge University where I specialized in Tropical Ecology. I am also a Data Scientist on the side. As a part of my research I have to carry out extensive data analysis, including spatial data analysis.or this purpose I prefer to use a combination of freeware tools- R, QGIS and Python.I domost of my spatial data analysis work using R and QGIS.Apart from being free, these are very powerful tools for data visualization, processing and analysis. I also hold an MPhil degree in Geography and Environment from Oxford University. I have honed my statistical and data analysis skills through a number of MOOCs including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R based Machine Learning course offered by Standford online). In addition to spatial data analysis, I am also proficient in statistical analysis, machine learning and data mining. I also enjoy general programming, data visualization and web development. In addition to being ascientist and number cruncher, I am an avid traveler

Machine Learning with Python by Sentdex (2016)

4.6 (15 Reviews)

Provider: YouTube
Time: 19h

Free

Practical Deep Learning for Coders, v3 (2019)

4.3 (20 Reviews)

Provider: fast.ai
Time: 30h

Free

Applied Machine Learning in Python (2016)

4.9 (481 Reviews)

Provider: Coursera
Time: 7h

Free

More Courses

More courses by Minerva Singh

Project Based Python Programming For Kids & Beginners

Project Based Python Programming For Kids & Beginners (2018)
4.6 (382 Reviews)

- Provider: Udemy
- Time: 5h

$11.99

Regression Analysis for Statistics & Machine Learning in R

Regression Analysis for Statistics & Machine Learning in R (2021)
4.6 (295 Reviews)

- Provider: Udemy
- Time: 7.5h

$11.99

Core Spatial Data Analysis: Introductory GIS with R and QGIS

Core Spatial Data Analysis: Introductory GIS with R and QGIS (2021)
4.4 (288 Reviews)

- Provider: Udemy
- Time: 2.5h

$11.99

Data Science:Data Mining & Natural Language Processing in R

Data Science:Data Mining & Natural Language Processing in R (2021)
4.6 (196 Reviews)

- Provider: Udemy
- Time: 13h

$11.99

[Intermediate] Spatial Data Analysis with R, QGIS & More

[Intermediate] Spatial Data Analysis with R, QGIS & More (2021)
4.7 (170 Reviews)

- Provider: Udemy
- Time: 5h

$11.99

Species Distribution Models with GIS & Machine Learning in R

Species Distribution Models with GIS & Machine Learning in R (2021)
4.8 (159 Reviews)

- Provider: Udemy
- Time: 3.5h

$11.99

All courses by Minerva Singh

Reviews

4.7

99 total reviews

5 star 4 star 3 star 2 star 1 star

Write a Review

By Israt Mithila

A lot of great info in a short amount of time! Thanks a lot Madam!

By Sakib Nayem

This course is very cool and interesting. One improvement that could be made is to have some more quizzes or tests throughout. I’m happy to see how the techniques can be practically used in the real world.

By Mon Amar

Overall a great course! As always, from the Friendly Teacher! The intuition tutorials are very helpful conceptually. The material is very professional.

By Haydi Lux

This is awesome course. I learned a lot from it. Thanks for providing the useful course.

By Devid Bekham

My suggestion is to add a few additional exercises between each lecture and with some way of testing after each module. It will makes learning fun and more engaging. Amazing pace of lectures and useful examples of each concept given. I enjoyed listening to these concepts.

By Sonakhhi Riyana

Simple and straight to the point. In depth but not too theoretical, so everyone can follow along quite easily. Recommend it for every students who are new to the field.

By Amaborsha Purnima

Super introduction to some various clustering methods. A lot of material covered in a small amount of time. I think it will be a great help for my future research tasks. Thanks A lot

By Choco Rio Queen

Overall a great course! Course lecture build-up from start to finish was very systematic and organized, along with the notebooks and additional material. I took away a ton of learning and knowledge, was more than I could have expected. I will use this course, its explanations and teaching as a reference to come back to always.

By Melissa M Runyon

An excellent, well thought out course.

By Rimon Bazu

Without boring and Fully Impressive Course. The instructor has made some tough concepts in machine learning easy to learn.

By Tarunner Joy

Awesome organized course going from classical to modern algorithms. The exercises were really useful. Would be great to see more applications to real world problems in the future.

By Chondro Kanta

Although I'm pretty experienced with machine learning algorithms, I found the course to be very useful in providing valuable insights. This is a Too much recommended course for machine learning student