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Personalized learning and Career guidance in Data Science We are here to help you in your Data Science journey.
We are a group of passionate folks having education from institutes like IIT, and having 10+ years of combined Industry experience. We provide customized guidance which includes Resume preparation, Profile building, and Data Science training, based on your career goals. Reach out to us on [email protected]
Always here to help you:)
Reinforcement learning best explained 😁
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Source - Your Animal Welfare Science (Twitter)
08/09/2020
Today we learn 'Unsupervised Learning'.
Unsupervised learning is when an algorithm can find some structure in the data by itself, without any label training.
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Example - Like if you are given a basket of fruits, you can 'cluster' them automatically into different fruits, without even knowing which fruit is which.
Similarly, you can classify news into sports vs politics vs others without telling the algorithm any labeled samples.
Similarly, you can predict what products are normally bought together (like bread with milk).
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06/09/2020
Did you notice this too?
A picture is worth a thousand words.
We at focus on conceptual clarity in Data Science, by intuitive explanations to Machine Learning concepts.
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02/09/2020
Today we learn 'Supervised Learning',
One of the famous types of Machine Learning.
Supervised learning is nothing but training an algorithm, by giving it examples of real world data, labelled by humans.
If you provide enough images of Dogs and enough images of Cats to an algorithm, it will, with good accuracy predict whether a 'new picture' is of Dog or Cat.
Similarly you can train your algorithm to detect humans in a CCTV footage.
Liked it? Let us know what would you like to learn more.
01/09/2020
How most of the AI and ML solutions look like😀
1. Manual rules, or
2. Single decision tree, or
3. Random Forest (ensemble of trees)
But the magic lies in, can you do it effectively?
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Source - Twitter
31/08/2020
Median is a 'resistant' measure of a distribution's centre, whereas mean/average can be affected by outliers, as in salary data, huge salary of a CEO can affect the average salary of the company. So we take median in that case.
Found this wonderful meme.
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30/08/2020
Ever heard of terms like
Left/negative skewed, and Right/positive skewed distribution?
Here is a visualization for you.
With how mean, median, and mode are affected in each type of data distribution.
We will later get into details of what each of these mean.
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22/08/2020
Know your data.
You have a file and you want a basic summary quickly. How to do that?
Just run this in Python, with few lines of code and you GET it. Famous library Pandas.
Next time we will get into Data Manipulation and Exporting data back to files.
09/08/2020
Next time if someone asks about normal distributions:)