Category: MLcourse

Bonus Project – Obesity Predictor – ML Course

July 19, 2018 / Manas Hejmadi

Hey Guys! I am back with another freshly brewed article for you guys! Today will be a practical project! So enjoy. This is Manas from csopensource.com – “Your one stop destination for everything computer science”. Today we will be making a project on Obesity Classification. Prelude Today I am back

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Day 8: K-Nearest Neighbors Classifier (kNN)

July 7, 2018 / Manas Hejmadi

Introduction After learning Support Vector Machines we are going to advance into the territory of kNN a.k.a KNearestNeighbors. K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions). kNN has been used in statistical estimation and

ai, csopensource, DL, kNN, ML, MLCOURSE

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Day 7: Support Vector Machines (SVM)

July 7, 2018 / Manas Hejmadi

Introduction Mastering Machine Learning is not that difficult, you just need a lot of time and effort to do so. Many young learners often start with classification or regression as it is the easiest and then hesitate to move forward into the more complex forms of ML. Hello World! This

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Day 6: Linear Regression

June 24, 2018 / Manas Hejmadi

Introduction In the ML Pipeline, Regression is the next step after Classification. We are going to specifically discuss about a subset of Regression called Linear regression. Linear regression is an approach to create a model to understand the relationship between input and output numerical variables. It helps one to understand

ai, csopensource, DL, how to do regression, ML, python, regression

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Day 5 || Classification: The “Hello World” of ML ||

June 10, 2018 / Manas Hejmadi

Prelude Classification is one of the simplest forms of ML, yet one of the most used. It is very simple to learn and the complexity is not that high. Classification can be used in many places with very or few changes made to the actual architecture, today we will be

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Day 4: Before We Start! || ML Crash Course

May 30, 2018 / Manas Hejmadi

Prelude We are very close to learning our first form of Classical Machine Learning which is Classification. However, before starting it we need a skeleton to work on. That skeleton is provided by python. There are mainly 3 languages for ML Development: Python, R & AIML. R is a bit

ai, csopensource, DL, ML, MLCOURSE

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Day 3: Practical Applications of Machine Learning || ML Crash Course

May 27, 2018 / Manas Hejmadi

Computers have played a very big role in our lives in the past 2 decades. In the past decade there have been numerous improvements in technology, thus Large Scale Machine Learning became feasible for companies. Now Machine Learning is practically in every part of our lives. In this post you

ai, Applications of Machine Learning, Applications of ML, csopensource, DL, Machine Learning, ML, Uses of Machine Learning, Uses of ML

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Day 2: Supervised Learning || ML Crash Course

May 26, 2018 / Manas Hejmadi

Prelude Machine Learning on its own is a very big topic to cover, but there is a distinct feature that divides all the models under Machine learning into two groups, Supervised Machine Learning and Unsupervised Machine Learning. That distinct feature is the availability of labelled data. Supervised Learning is the

ai, csopensource, DL, Machine Learning, ML, Supervised Learning, Unsupervised Learning

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Day 1: What is Machine Learning? – ML Crash Course

May 24, 2018 / Manas Hejmadi

First of all, let us start with the Definition and basic intuition of the concept of Machine Learning! Machine Learning is a subset of Scientific Computing, where problems that are almost impossible to solve manually by a human are solved with ease. So let us learn about all the concepts

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Day 0: Getting your mind ready – ML Crash Course

May 23, 2018 / Manas Hejmadi

Hey Guys! This is Manas from csopensource.com – “Your one-stop destination for everything computer science” and welcome to my Machine Learning Crash Course. This course is designed to be appealing even for the people with no coding experience whatsoever. Prelude With so much hype around Machine Learning, one would think

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