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Data Science & Machine Learning
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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free

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Which of the following is an important library or framework for data visualization using PYTHON? [Not Machine learning]
Anonymous Quiz
6%
Keras
13%
Tensorflow
71%
Matplotlib
10%
Scikit-leàrn
🔰Python Cheat Sheet for all Programmers🔰

Top 15 Cheat Sheets for Machine Learning, Data Science & Big Data

🖇Link : https://anonfiles.com/zcLcO0G5oc/Python_Top_15_Cheat_Sheets_for_Machine_Learning_Data_Science_Big_Data_rar

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Do you want a YouTube video on free certification courses to learn data science and machine Learning?
[Need at least 200 Yes on this poll]
Anonymous Poll
93%
Yes
7%
No
Data Science & Machine Learning pinned «Do you want a YouTube video on free certification courses to learn data science and machine Learning?
[Need at least 200 Yes on this poll]
»
Machine Learning Glossary
This glossary defines general machine learning terms, plus terms specific to TensorFlow
https://developers.google.com/machine-learning/glossary/#convolutional_neural_network
Visualization Cheat Sheet.pdf
1.5 MB
Data Visualization Cheat Sheet
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Coding and Aptitude Round before interview

Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.

Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.

Resources for Prep:

For algorithms and data structures prep,Leetcode and Hackerrank are good resources.

For aptitude prep, you can refer to IndiaBixand Practice Aptitude.

With respect to data science challenges, practice well on GLabs and Kaggle.

Brilliant is an excellent resource for tricky math and statistics questions.

For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.

Things to Note:

Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!

In case, you are finished with the test before time, recheck your answers and then submit.

Sometimes these rounds don’t go your way, you might have had a brain fade, it was not your day etc. Don’t worry! Shake if off for there is always a next time and this is not the end of the world.
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