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Title: GitHub - letscode-17/Data-Science-Interview-Resources: A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently. · GitHub

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Description: A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently. - letscode-17/Data-Science-Interview-Resources

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https://github.com/letscode-17/Data-Science-Interview-Resources#how-to-get-an-interview-
https://medium.com/@rbhatia46/essential-probability-statistics-concepts-before-data-science-bb787b7a5aefhttps://medium.com/@rbhatia46/essential-probability-statistics-concepts-before-data-science-bb787b7a5aef
https://github.com/letscode-17/Data-Science-Interview-Resources#some-tips-on-resumecv
Advice on building Data Portfolio Projectshttps://medium.com/@jasonkgoodman/advice-on-building-data-portfolio-projects-c5f96d8a0627
How to write a killer Software Engineering Resumehttps://www.freecodecamp.org/news/writing-a-killer-software-engineering-resume-b11c91ef699d/
Get your Data Science Resume past the ATShttps://towardsdatascience.com/up-level-your-data-science-resume-getting-past-ats-64322f0cbb73
How to write a developer résumé that hiring managers will actually readhttps://www.freecodecamp.org/news/how-to-write-a-resume-that-works/
https://github.com/letscode-17/Data-Science-Interview-Resources#probability-and-statistics
Understand the basics of Descriptive Statistics(Really Important for an interview)https://towardsdatascience.com/understanding-descriptive-statistics-c9c2b0641291
40 Question on probability for a Data Science Interviewhttps://www.analyticsvidhya.com/blog/2017/04/40-questions-on-probability-for-all-aspiring-data-scientists/
40 Statistics Interview Problems and Answers for Data Scientistshttps://towardsdatascience.com/40-statistics-interview-problems-and-answers-for-data-scientists-6971a02b7eee
Probability and Statistics in the context of Deep Learninghttps://towardsdatascience.com/probability-and-statistics-explained-in-the-context-of-deep-learning-ed1509b2eb3f
Probability v/s Likelihoodhttps://www.youtube.com/watch?v=pYxNSUDSFH4
Bootstrap Methods - The Swiss Army Knife of any Data Scientisthttps://medium.com/data-science-journal/the-bootstrap-the-swiss-army-knife-of-any-data-scientist-acd6e592be13
Confidence Intervals Explained Simply for Data Scientistshttps://mlwhiz.com/blog/2020/02/21/ci/
P-value Explained Simply for Data Scientistshttps://towardsdatascience.com/p-value-explained-simply-for-data-scientists-4c0cd7044f14
PDF is not a probabilityhttps://towardsdatascience.com/pdf-is-not-a-probability-5a4b8a5d9531
5 Sampling algorithms every Data Scientist should knowhttps://mlwhiz.com/blog/2019/07/30/sampling/
The 10 Statistical Techniques Data Scientists Need to Masterhttps://www.kdnuggets.com/2017/11/10-statistical-techniques-data-scientists-need-master.html
https://github.com/letscode-17/Data-Science-Interview-Resources#sql-and-data-acquisition
5 Common SQL Interview Problems for Data Scientistshttps://towardsdatascience.com/5-common-sql-interview-problems-for-data-scientists-1bfa02d8bae6
46 Questions to test a Data Scientist on SQLhttps://www.analyticsvidhya.com/blog/2017/01/46-questions-on-sql-to-test-a-data-science-professional-skilltest-solution/
30 SQL Interview Questions curated for FAANG by an Ex-Facebook Data Scientisthttps://www.nicksingh.com/posts/30-sql-and-database-design-questions-from-real-data-science-interviews
SQL Interview Questionshttps://365datascience.com/sql-interview-questions/
How to ace Data Science Interviews - SQLhttps://towardsdatascience.com/how-to-ace-data-science-interviews-sql-b71de212e433
3 Must Know SQL Questions to pass your Data Science Interviewhttps://medium.com/@jayfeng/three-must-know-sql-questions-to-pass-your-data-science-interview-463311c7eaea
10 frequently asked SQL Queries in Interviewshttps://www.java67.com/2013/04/10-frequently-asked-sql-query-interview-questions-answers-database.html
Technical Data Science Interview Questions: SQL and Codinghttps://hackernoon.com/technical-data-science-interview-questions-sql-and-coding-jv1k32bf
How to optimize SQL Queries - Datacamphttps://www.datacamp.com/community/tutorials/sql-tutorial-query
Ten SQL Concepts You Should Know for Data Science Interviewshttps://towardsdatascience.com/ten-sql-concepts-you-should-know-for-data-science-interviews-7acf3e428185
https://github.com/letscode-17/Data-Science-Interview-Resources#data-preparation-and-visualization
5 Feature Selection Algorithms every Data Scientist should knowhttps://towardsdatascience.com/the-5-feature-selection-algorithms-every-data-scientist-need-to-know-3a6b566efd2
6 Different Ways to Compensate for Missing Values In a Dataset https://towardsdatascience.com/6-different-ways-to-compensate-for-missing-values-data-imputation-with-examples-6022d9ca0779
A Brief Overview of Outlier Detection Techniqueshttps://towardsdatascience.com/a-brief-overview-of-outlier-detection-techniques-1e0b2c19e561
Cleaning and Prepping Data with Python for Data Science — Best Practices and Helpful Packageshttps://medium.com/@rrfd/cleaning-and-prepping-data-with-python-for-data-science-best-practices-and-helpful-packages-af1edfbe2a3
When to use which plot for visualizationhttps://towardsdatascience.com/what-plot-why-this-plot-and-why-not-9508a0cb35ea
Ways to detect and remove Outliershttps://towardsdatascience.com/ways-to-detect-and-remove-the-outliers-404d16608dba
Dealing with Class Imbalances in Machine Learninghttps://towardsdatascience.com/dealing-with-imbalanced-classes-in-machine-learning-d43d6fa19d2
Smarter ways to encode categorical datahttps://towardsdatascience.com/smarter-ways-to-encode-categorical-data-for-machine-learning-part-1-of-3-6dca2f71b159
Numpy and Pandas Cheatsheethttps://github.com/jessicayung/data-analyst-nd/blob/master/2-intro-to-data-analysis/numpy_pandas_cheatsheet.pdf
3 Methods to deal with outliershttps://www.kdnuggets.com/2017/01/3-methods-deal-outliers.html
Feature Selection Techniqueshttps://towardsdatascience.com/feature-selection-techniques-in-machine-learning-with-python-f24e7da3f36e
Why, how and When to scale your featureshttps://medium.com/greyatom/why-how-and-when-to-scale-your-features-4b30ab09db5e
Everything you need to know about Scatter plotshttps://towardsdatascience.com/everything-you-need-to-know-about-scatter-plots-for-data-visualisation-924144c0bc5
How to Select Features for Machine Learninghttps://www.youtube.com/watch?v=YaKMeAlHgqQ
10 ways for Feature Selectionhttps://www.youtube.com/watch?v=Erp0bjEPoM8
https://github.com/letscode-17/Data-Science-Interview-Resources#classic-machine-learning-algorithms
https://github.com/letscode-17/Data-Science-Interview-Resources#1-logistic-regression
All about Logistic Regression in one articlehttps://towardsdatascience.com/logistic-regression-b0af09cdb8ad
Understanding Logistic Regression step-by-stephttps://towardsdatascience.com/understanding-logistic-regression-step-by-step-704a78be7e0a
Logistic Regression - Short and Clear Explanation - 9 Minshttps://www.youtube.com/watch?v=yIYKR4sgzI8
Linear Regression vs Logistic Regressionhttps://www.youtube.com/watch?v=OCwZyYH14uw
30 Questions to test a Data Scientist on Logistic Regressionhttps://www.analyticsvidhya.com/blog/2017/08/skilltest-logistic-regression/
Logistic Regression - Understand Everything (Theory + Maths + Coding) in 1 videohttps://www.youtube.com/watch?v=VCJdg7YBbAQ
https://github.com/letscode-17/Data-Science-Interview-Resources#2-linear-regression
30 Questions to test a Data Scientist on Linear Regressionhttps://www.analyticsvidhya.com/blog/2017/07/30-questions-to-test-a-data-scientist-on-linear-regression/
Linear Regression - Understand Everything (Theory + Maths + Coding) in 1 videohttps://www.youtube.com/watch?v=E5RjzSK0fvY
5 Types of Regression and their propertieshttps://towardsdatascience.com/5-types-of-regression-and-their-properties-c5e1fa12d55e
Ridge Regression - Clearly Explainedhttps://www.youtube.com/watch?v=Q81RR3yKn30
Lasso Regression - Clearly Explainedhttps://www.youtube.com/watch?v=NGf0voTMlcs
https://github.com/letscode-17/Data-Science-Interview-Resources#3-tree-basedensemble-algorithms
30 Questions to test a Data Scientist on Tree based modelshttps://www.analyticsvidhya.com/blog/2017/09/30-questions-test-tree-based-models/
Gini-index v/s Information Entropyhttps://towardsdatascience.com/gini-index-vs-information-entropy-7a7e4fed3fcb
Decision Tree vs. Random Forest – Which Algorithm Should you Use?https://www.analyticsvidhya.com/blog/2020/05/decision-tree-vs-random-forest-algorithm/
Why Random Forest doesn't work well for Time-Series?https://medium.com/datadriveninvestor/why-wont-time-series-data-and-random-forests-work-very-well-together-3c9f7b271631
Comprehensive guide to Ensemble Modelshttps://www.analyticsvidhya.com/blog/2018/06/comprehensive-guide-for-ensemble-models/
The Simple Math behind 3 Decision Tree Splitting criterionshttps://mlwhiz.com/blog/2019/11/12/dtsplits/
https://github.com/letscode-17/Data-Science-Interview-Resources#4-k-nearest-neighbors
Fundamental Interview Questions on KNN - A Quick refreshhttp://theprofessionalspoint.blogspot.com/2019/01/knn-algorithm-in-machine-learning.html
30 Questions to test a Data Scientist on KNNhttps://www.analyticsvidhya.com/blog/2017/09/30-questions-test-k-nearest-neighbors-algorithm/
Pros and Cons of KNNhttps://www.fromthegenesis.com/pros-and-cons-of-k-nearest-neighbors/
KNN Algorithm - Understand Everything (Theory + Maths + Coding) in 1 videohttps://www.youtube.com/watch?v=6kZ-OPLNcgE
https://github.com/letscode-17/Data-Science-Interview-Resources#5-support-vector-machines
All about SVMs - Math, Terminology, Intuition, Kernels in one articlehttps://towardsdatascience.com/support-vector-machines-svm-c9ef22815589
25 Questions to test a Data Scientist on SVMshttps://www.analyticsvidhya.com/blog/2017/10/svm-skilltest/
https://github.com/letscode-17/Data-Science-Interview-Resources#6-naive-bayes
12 tips to make most out of Naive Bayeshttps://machinelearningmastery.com/better-naive-bayes/
Naive Bayes - Understand Everything (Theory + Maths + Coding) in 1 videohttps://www.youtube.com/watch?v=vz_xuxYS2PM
6 easy steps to learn Naive Bayeshttps://www.analyticsvidhya.com/blog/2017/09/naive-bayes-explained/
https://github.com/letscode-17/Data-Science-Interview-Resources#time-series
40 Questions to test a Data Scientist on Time Serieshttps://www.analyticsvidhya.com/blog/2017/04/40-questions-on-time-series-solution-skillpower-time-series-datafest-2017/
11 Classical Time Series Forecasting Methodshttps://machinelearningmastery.com/time-series-forecasting-methods-in-python-cheat-sheet/
Interview Questions on ARIMAhttps://www.youtube.com/watch?v=654SjiZO5ks
https://github.com/letscode-17/Data-Science-Interview-Resources#unsupervised-learning
The DOs and DONTs of PCA(Principal Component Analysis)https://medium.com/@sadatnazrul/the-dos-and-donts-of-principal-component-analysis-7c2e9dc8cc48
An introduction to t-SNE : DataCamphttps://www.datacamp.com/community/tutorials/introduction-t-sne
Dimensionally Reducing Squeezing out the good stuffhttps://www.youtube.com/watch?v=4QMFNg7tjbk
Dimensionality Reduction for Dummies : Part 1 - Intuitionhttps://towardsdatascience.com/https-medium-com-abdullatif-h-dimensionality-reduction-for-dummies-part-1-a8c9ec7b7e79
In-depth Explanation of DBSCAN Algorithmhttps://towardsdatascience.com/explaining-dbscan-clustering-18eaf5c83b31
https://github.com/letscode-17/Data-Science-Interview-Resources#recommender-systems
Recommender Systems in a Nutshellhttps://www.kdnuggets.com/2020/07/recommender-systems-nutshell.html
https://github.com/letscode-17/Data-Science-Interview-Resources#deep-learning
Why Regularization reduces overfitting in Deep Neural Networkshttps://www.youtube.com/watch?v=4nqD5TBlOWU
Pros and Cons of Neural Networkshttps://towardsdatascience.com/hype-disadvantages-of-neural-networks-6af04904ba5b
When not to use Neural Networkshttps://medium.com/datadriveninvestor/when-not-to-use-neural-networks-89fb50622429
40 Questions to test a Data Scientist on Deep learninghttps://www.analyticsvidhya.com/blog/2017/04/40-questions-test-data-scientist-deep-learning/
21 Popular Deep Learning Interview Questionshttps://www.analyticsvidhya.com/blog/2020/04/comprehensive-popular-deep-learning-interview-questions-answers/
Deep Learning Interview Questions - Edurekahttps://www.youtube.com/watch?v=HGXlFG_Rz4E
Activation Functions in a Neural Network - Explainedhttps://towardsdatascience.com/activation-functions-neural-networks-1cbd9f8d91d6
Vanishing and Exploding Gradient - Clearly Explainedhttps://www.youtube.com/watch?v=qO_NLVjD6zE
Bias and Variance - Very clearly explainedhttps://www.youtube.com/watch?v=EuBBz3bI-aA
Why use ReLU over Sigmoidhttps://stats.stackexchange.com/questions/126238/what-are-the-advantages-of-relu-over-sigmoid-function-in-deep-neural-networks
25 Deep Learning Interview Qurstions to test your knowledgehttps://towardsdatascience.com/50-deep-learning-interview-questions-part-1-2-8bbc8a00ec61
10 Deep Learning Best Practices to Keep in Mind in 2020https://nanonets.com/blog/10-best-practices-deep-learning/
https://github.com/letscode-17/Data-Science-Interview-Resources#machine-learning-interpretability
Four Questions on Deciphering the World of Machine Learning Modelshttps://narrativescience.com/resource/blog/machine-learning-models/
Machine Learning Explanaibility - Crash Course by Kagglehttps://www.kaggle.com/learn/machine-learning-explainability
SHAP Values explained simplyhttps://www.youtube.com/watch?v=VB9uV-x0gtg
https://github.com/letscode-17/Data-Science-Interview-Resources#case-studies
Dawn of Taxi Aggregatorshttps://www.analyticsvidhya.com/blog/2016/04/case-study-analytics-interviews-dawn-taxi-aggregators/
Optimizing product prices for an online vendorhttps://www.analyticsvidhya.com/blog/2016/07/solving-case-study-optimize-products-price-online-vendor-level-hard/
Tips for a Case-Study Interviewhttps://workera.ai/resources/data-science-case-study-interview/
Mercari Price Predictionhttps://towardsdatascience.com/a-data-science-case-study-with-python-mercari-price-prediction-4e852d95654
End-to-End multiclass Text Classification pipelinehttps://mlwhiz.com/blog/2020/05/24/multitextclass/
End-to-End multiclass Image Classification pipelinehttps://mlwhiz.com/blog/2020/06/06/multiclass_image_classification_pytorch/
Large Scale Forecasting for 1000+ products - Nagarrohttps://www.youtube.com/watch?v=8jfDBD6xlFM
Clustering and Classification in E-Commercehttps://lucidworks.com/post/clustering-classification-supervised-unsupervised-learning-ecommerce/
The ABCs of Learning to Rankhttps://lucidworks.com/post/abcs-learning-to-rank/
Data Science Case Study: Optimizing Product Placement in Retail https://towardsdatascience.com/data-science-case-study-optimizing-product-placement-in-retail-part-1-2e8b27e16e8d
https://github.com/letscode-17/Data-Science-Interview-Resources#nlp
30 Questions to test a Data Scientist on NLPhttps://www.analyticsvidhya.com/blog/2017/07/30-questions-test-data-scientist-natural-language-processing-solution-skilltest-nlp/
11 Most Commonly Asked NLP Interview Questions For Beginnershttps://analyticsindiamag.com/11-most-commonly-asked-nlp-interview-questions-for-beginners/
How to solve 90% of NLP Problemshttps://blog.insightdatascience.com/how-to-solve-90-of-nlp-problems-a-step-by-step-guide-fda605278e4e
Questions asked for NLP Roles at Companieshttps://medium.com/modern-nlp/nlp-interview-questions-f062040f32f7
https://github.com/letscode-17/Data-Science-Interview-Resources#data-science-interviews-at-faang-and-similar-companies
Amazon’s Data Scientist Interview Practice Problemshttps://towardsdatascience.com/amazon-data-scientist-interview-practice-problems-15b9b86e86c6
Microsoft Data Science Interview Questions and Answershttps://towardsdatascience.com/microsoft-data-science-interview-questions-and-answers-69ccac16bd9b
Problem Solving Questions for Data Science interview at Googlehttps://towardsdatascience.com/googles-data-science-interview-brain-teasers-7f3c1dc4ea7f
https://github.com/letscode-17/Data-Science-Interview-Resources#becoming-a-rockstar-data-scientistread-if-you-have-extra-time
Top 13 Skills To Become a Rockstar Data Scientisthttps://towardsdatascience.com/top-13-skills-to-become-a-rockstar-data-scientist-faf2f97e655d
Understand these 4 ML concepts to sound like a masterhttps://towardsdatascience.com/understand-these-4-advanced-concepts-to-sound-like-a-machine-learning-master-d32843840b52
12 things I wish I knew before starting as a Data Scientisthttps://medium.com/deliberate-data-science/12-things-i-wish-id-known-before-starting-as-a-data-scientist-45989be6300e
Understand the Data Science pipelinehttps://towardsdatascience.com/a-beginners-guide-to-the-data-science-pipeline-a4904b2d8ad3
Kaggle Data Science Glossaryhttps://www.kaggle.com/shivamb/data-science-glossary-on-kaggle
Google Machine Learning Glossaryhttps://developers.google.com/machine-learning/glossary/
Running your ML Predictions 50 times faster - Hummingbirdhttps://mlwhiz.com/blog/2020/06/06/hummingbird_faster_ml_preds/
3 Mistakes you should not make in a Data Science Interviewhttps://mlwhiz.com/blog/2019/12/24/mistakes/
How to find Feature importances for BlackBox Models?https://mlwhiz.com/blog/2019/12/04/blackbox/
https://github.com/letscode-17/Data-Science-Interview-Resources#data-structures-and-algorithmsoptional
A Data Scientist's guide to Data Structures and Algorithmshttps://towardsdatascience.com/a-data-scientists-guide-to-data-structures-algorithms-1176395015a0
Handling Trees in Data Science Algorithmic Interviewhttps://towardsdatascience.com/handling-trees-in-data-science-algorithmic-interview-ea14dd1b6236
A simple introduction to Linked Lists for Data Scientistshttps://mlwhiz.com/blog/2020/01/28/ll/
Dynamic Programming for Data Scientistshttps://mlwhiz.com/blog/2020/01/28/dp/
3 Programming concepts for Data Scientistshttps://mlwhiz.com/blog/2019/12/09/pc/
Data Scientists, The 5 Graph Algorithms that you should knowhttps://mlwhiz.com/blog/2019/09/02/graph_algs/
https://github.com/letscode-17/Data-Science-Interview-Resources#engineering-and-deployment
A Layman’s Guide for Data Scientists to create APIs in minuteshttps://mlwhiz.com/blog/2020/06/06/fastapi_for_data_scientists/
Take your Machine Learning Models to Production with these 5 simple stepshttps://mlwhiz.com/blog/2019/12/25/prod/
2 way to deploy your ML modelshttps://towardsdatascience.com/there-are-two-very-different-ways-to-deploy-ml-models-heres-both-ce2e97c7b9b1
How to deploy a Keras model as a web app through Flaskhttps://towardsdatascience.com/deploying-a-keras-deep-learning-model-as-a-web-application-in-p-fc0f2354a7ff
How to write Web apps using simple Python for Data Scientists?https://towardsdatascience.com/how-to-write-web-apps-using-simple-python-for-data-scientists-a227a1a01582
https://github.com/letscode-17/Data-Science-Interview-Resources#big-data-and-spark
55 Apache Spark Interview Questionshttps://www.edureka.co/blog/interview-questions/top-apache-spark-interview-questions-2016/
10 Questions you can expect in a Spark Interviewhttps://medium.com/analytics-vidhya/10-questions-you-can-expect-in-spark-interview-24b89b807dfb
Hive Interview Questionshttps://www.tutorialspoint.com/hive/hive_interview_questions.htm
Top 20 Apache Spark Interview Questionshttps://www.youtube.com/watch?v=Y8LKEDyA5iY
Spark Interview Questions - The entire playlisthttps://www.youtube.com/playlist?list=PLtfmIPhU2DkNjQjL08kR3cd4kUzWqS0vg
Another fabulous Playlist for Spark Interview Questionshttps://www.youtube.com/playlist?list=PL9sbKmQTkW05mXqnq1vrrT8pCsEa53std
Practical PySpark tips for Data Scientistshttps://towardsdatascience.com/practical-spark-tips-for-data-scientists-145d85e9b2d8
3 Ways to parallelize your code using Sparkhttps://towardsdatascience.com/3-methods-for-parallelization-in-spark-6a1a4333b473
Datashader - Revealing the Structure of Genuinely Big Datahttps://www.youtube.com/watch?v=6m3CFbKmK_c
Lightnings Talk : What one should know about Spark-MLlibhttps://www.youtube.com/watch?v=DBxcua0Vmvk
Solving “Container Killed by Yarn For Exceeding Memory Limits” Exception in Apache Sparkhttps://medium.com/analytics-vidhya/solving-container-killed-by-yarn-for-exceeding-memory-limits-exception-in-apache-spark-b3349685df16
https://github.com/letscode-17/Data-Science-Interview-Resources#some-amazing-stuff-on-python-and-spark
Improving Python and Spark performancehttps://www.youtube.com/watch?v=qIKImANLFtE
High Performance Python on Sparkhttps://www.youtube.com/watch?v=abZ0f5ug18U
Vectorized UDFs: Scalable Analysis with Python and PySparkhttps://www.youtube.com/watch?v=Til-StSDvfA
https://github.com/letscode-17/Data-Science-Interview-Resources#general-interview-questions-across-the-spectrum-video
Common Data Science Interview Questions - Edurekahttps://www.youtube.com/watch?v=tTAieUcNHdY
Common Machine Learning Interview Question - Edurekahttps://www.youtube.com/watch?v=t6gOpFLt-Ks
Top 5 algorithms used in Data Sciencehttps://www.youtube.com/watch?v=BfowBtIxNu4
Common Data Science Interview Questions - Analytics Universityhttps://www.youtube.com/watch?v=BfowBtIxNu4
3 types of Data Science Interview Questionshttps://www.youtube.com/watch?v=4Z6lxfglvUU
Lessons learned the hard way - Hacking the Data Science Interviewhttps://www.youtube.com/watch?v=3BRLGRqj8p
What it's like to Interview as a Data Scientisthttps://www.youtube.com/watch?v=0HmAEWPfMnM
5 Tips for getting a Data Science Jobhttps://www.youtube.com/watch?v=MfP-P8EHGBo
8 Frequently used Data Science Algorithmshttps://www.youtube.com/watch?v=z3wMgOTSE5s
Scenario Based Practical Interviewhttps://www.youtube.com/watch?v=bJPhEa3mbwo
KNN v/s K Meanshttps://www.youtube.com/watch?v=OClrEI_5Ri4
https://github.com/letscode-17/Data-Science-Interview-Resources#general-interview-questions-across-the-spectrum-reading
The Data Science Interview Guidehttps://towardsdatascience.com/data-science-interview-guide-4ee9f5dc778
Top 30 Data Science Interview Questionshttps://towardsdatascience.com/top-30-data-science-interview-questions-7dd9a96d3f5c
35 Important Data Science Interview Questionshttps://www.edureka.co/blog/interview-questions/data-science-interview-questions/
100 Data Science Interview Questions across FAANGhttps://medium.com/@e22aafa7d95/c5a66186769a
The Most Comprehensive Data Science Interview Guidehttps://www.analyticsvidhya.com/blog/2018/06/comprehensive-data-science-machine-learning-interview-guide/
41 essential ML interview questions - Springboardhttps://www.springboard.com/blog/machine-learning-interview-questions/
30 days of Data Science Interview Preparation - iNeuronhttps://github.com/iNeuronai/interview-question-data-science-
109 Data Science Interview Questions - Springboardhttps://www.springboard.com/blog/data-science-interview-questions/
Most asked Data Science interview questions in India - Springboardhttps://in.springboard.com/blog/most-asked-data-science-interview-questions-in-india/
List of AI Startups in India and resources for preparing for the interviewhttps://github.com/theainerd/MLInterview
5 interview questions to predict a good Data Scientisthttps://medium.com/predict/five-interview-questions-to-predict-a-good-data-scientist-40d310cdcd68
8 proven ways to improve the accuracy of your ML model https://www.analyticsvidhya.com/blog/2015/12/improve-machine-learning-results/
60 Interview Questions on Machine Learning - AnalyticsIndiaMaghttps://analyticsindiamag.com/60-interview-questions-on-machine-learning/
The Big List of DS and ML interview Resourceshttps://towardsdatascience.com/the-big-list-of-ds-ml-interview-resources-2db4f651bd63
100 Basic Data Science Interview Questions along with answershttps://www.dezyre.com/article/100-data-science-interview-questions-and-answers-general-for-2018/184
40 interview questions asked at Startups in ML/DS Interviewhttps://www.analyticsvidhya.com/blog/2016/09/40-interview-questions-asked-at-startups-in-machine-learning-data-science/
My Data Science/Machine Learning Job Interview Experience : List of DS/ML/DL Questions – Machine Learning in Actionhttps://appliedmachinelearning.blog/2018/04/13/my-data-science-machine-learning-job-interview-experience-list-of-ds-ml-dl-questions/
How do I prepare for a Data Science phone interview at Airbnbhttps://www.quora.com/How-do-I-prepare-for-a-phone-interview-for-a-data-scientist-position-with-Airbnb
Best ML algorithm for regression problemshttps://towardsdatascience.com/selecting-the-best-machine-learning-algorithm-for-your-regression-problem-20c330bad4ef
How to ace the In person Data Science Interviewhttps://towardsdatascience.com/how-to-ace-the-in-person-data-science-interview-584ca11df08a
How to land a Data Scientist job at Airbnbhttps://towardsdatascience.com/how-to-land-a-data-scientist-job-at-your-dream-company-my-journey-to-airbnb-f6a1e99892e8
120 Data Science Interview Questions(from all domains)https://github.com/kojino/120-Data-Science-Interview-Questions
Understanding the Bias-Variance Tradeoffhttps://towardsdatascience.com/understanding-the-bias-variance-tradeoff-165e6942b229
You Need these Cheatsheets if you are tackling ML algorithmshttps://medium.freecodecamp.org/you-need-these-cheat-sheets-if-youre-tackling-machine-learning-algorithms-45da5743888e
Red Flags in a Data Science Interviewhttps://towardsdatascience.com/red-flags-in-data-science-interviews-4f492bbed4c4
A Data Scientist's take on Interview Questionshttps://towardsdatascience.com/my-take-on-data-scientist-interview-questions-part-1-6df22252b2e8
What is Cross Entropy(Nice and Short Explanation)https://stackoverflow.com/questions/41990250/what-is-cross-entropy/41990932#41990932
What does an ideal Data Scientist's profile look likehttps://towardsdatascience.com/what-does-an-ideal-data-scientists-profile-look-like-7d7bd78ff7ab
25 Fun Questions for a Machine Learning interviewhttps://medium.com/analytics-vidhya/25-fun-questions-for-a-machine-learning-interview-373b744a4faa
How to Prepare for Machine Learning Interviewshttps://towardsdatascience.com/how-to-prepare-for-machine-learning-interviews-5fac3db58168
How to develop a Machine Learning Model from scratchhttps://towardsdatascience.com/machine-learning-general-process-8f1b510bd8af
End to End guide for a Machine Learning Projecthttps://medium.com/fintechexplained/end-to-end-guide-for-machine-learning-project-146c288186dc
Classification v/s Regressionhttps://medium.com/fintechexplained/supervised-machine-learning-regression-vs-classification-18b2f97708de
Must Know mathematical measures for Every Data Scientisthttps://medium.com/fintechexplained/must-know-mathematical-measures-for-data-scientist-15bfc4f7f39c
Where did the least square come fromhttps://towardsdatascience.com/where-did-the-least-square-come-from-3f1abc7f7caf
Regularization in Machine Learning - Explainedhttps://towardsdatascience.com/regularization-in-machine-learning-76441ddcf99a
https://github.com/letscode-17/Data-Science-Interview-Resources#interesting-reads
3 Common Data Science Career Transitions and how to make them happenhttps://towardsdatascience.com/3-common-data-science-career-transitions-and-how-to-make-them-happen-588c3618942f
Navigating the Data Science Career Landscapehttps://hackernoon.com/navigating-the-data-science-career-landscape-db746a61ac62
Which model and how much datahttps://towardsdatascience.com/which-model-and-how-much-data-75a3999660f3
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