Feature Grokking Interviews on the homepage card grid

Author: singhsidhukuldeep

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-</style> <h1 id=crack-data-science-interviews>Crack <strong>Data Science</strong> Interviews</h1> <div class="grid cards"> <ul> <li> <details class=interview-questions> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> Interview Questions</summary> <hr> <p>These are currently most commonly asked interview questions.</p> <p>Questions can be removed if they are no longer popular in interview circles and added as new question banks are released.</p> <ul> <li><a href=flashcards/ class=glowing-link>📇 Flashcards</a></li> <li><a href=Interview-Questions/data-structures-algorithms/ >DSA (Data Structures &amp; Algorithms)</a></li> <li><a href=Interview-Questions/System-design/ >System Design</a></li> <li><a href=Interview-Questions/Natural-Language-Processing/ >Natural Language Processing (NLP)</a></li> <li><a href=Interview-Questions/Probability/ >Probability</a></li> <li><a href=Interview-Questions/AB-testing/ >A/B Testing</a></li> <li><a href=Interview-Questions/SQL-Interview-Questions/ >SQL</a></li> <li><a href=Interview-Questions/Machine-Learning/ >ML-Algorithms</a></li> <li><a href=Interview-Questions/Python/ >Python</a></li> <li><a href=Interview-Questions/Pandas/ >Pandas</a></li> <li><a href=Interview-Questions/NumPy/ >NumPy</a></li> <li><a href=Interview-Questions/Scikit-Learn/ >Scikit-Learn</a></li> <li><a href=Interview-Questions/LangChain/ >LangChain</a></li> <li><a href=Interview-Questions/LangGraph/ >LangGraph</a></li> <li><a href=Interview-Questions/Forward-Deployed-Engineer/ >Forward Deployed Engineer (FDE)</a></li> <li><a href=Interview-Questions/Interview-Question-Resources/ >Interview Question Resources</a> - <strong>Community-curated sources for all topics</strong></li> </ul> </details> </li> <li> <details class=cheat-sheet> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> <strong>Cheat Sheets</strong></summary> <hr> <p>Distilled down important concepts for your quick reference</p> <ul> <li><a href=Cheat-Sheets/Django/ >Django</a></li> <li><a href=Cheat-Sheets/Flask/ >Flask</a></li> <li><a href=Cheat-Sheets/Hypothesis-Tests/ >Hypothesis-Tests</a></li> <li><a href=Cheat-Sheets/Keras/ >Keras</a></li> <li><a href=Cheat-Sheets/LangChain-LangGraph/ >LangChain-LangGraph</a></li> <li><a href=Cheat-Sheets/NumPy/ >NumPy</a></li> <li><a href=Cheat-Sheets/Pandas/ >Pandas</a></li> <li><a href=Cheat-Sheets/PySpark/ >PySpark</a></li> <li><a href=Cheat-Sheets/PyTorch/ >PyTorch</a></li> <li><a href=Cheat-Sheets/Python/ >Python</a></li> <li><a href=Cheat-Sheets/RegEx/ >RegEx</a></li> <li><a href=Cheat-Sheets/Sk-learn/ >Sk-learn</a></li> <li><a href=Cheat-Sheets/SQL/ >SQL</a></li> <li><a href=Cheat-Sheets/tensorflow/ >tensorflow</a></li> </ul> </details> </li> <li> <details class=ml-algo> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> <strong>ML Algorithms</strong></summary> <hr> <p>From scratch implementation and documentation of all ML algorithms</p> <ul> <li><a href=Machine-Learning/ARIMA/ >ARIMA</a></li> <li><a href=Machine-Learning/Activation%20functions/ >Activation functions</a></li> <li><a href=Machine-Learning/Collaborative%20Filtering/ >Collaborative Filtering</a></li> <li><a href=Machine-Learning/Confusion%20Matrix/ >Confusion Matrix</a></li> <li><a href=Machine-Learning/DBSCAN/ >DBSCAN</a></li> <li><a href=Machine-Learning/Decision%20Trees/ >Decision Trees</a></li> <li><a href=Machine-Learning/Gradient%20Boosting/ >Gradient Boosting</a></li> <li><a href=Machine-Learning/K-means%20clustering/ >K-means clustering</a></li> <li><a href=Machine-Learning/Linear%20Regression/ >Linear Regression</a></li> <li><a href=Machine-Learning/Logistic%20Regression/ >Logistic Regression</a></li> <li><a href=Machine-Learning/Loss%20Function%20MAE%2C%20RMSE/ >Loss Function MAE, RMSE</a></li> <li><a href=Machine-Learning/Neural%20Networks/ >Neural Networks</a></li> <li><a href=Machine-Learning/Normal%20Distribution/ >Normal Distribution</a></li> <li><a href=Machine-Learning/Normalization%20Regularisation/ >Normalization Regularisation</a></li> <li><a href=Machine-Learning/Overfitting%2C%20Underfitting/ >Overfitting, Underfitting</a></li> <li><a href=Machine-Learning/PCA/ >PCA</a></li> <li><a href=Machine-Learning/Random%20Forest/ >Random Forest</a></li> <li><a href=Machine-Learning/Support%20Vector%20Machines/ >Support Vector Machines</a></li> <li><a href=Machine-Learning/Unbalanced%2C%20Skewed%20data/ >Unbalanced, Skewed data</a></li> <li><a href=Machine-Learning/kNN/ >kNN</a></li> </ul> </details> </li> <li> <details class=online-resources> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> <strong>Online Resources</strong></summary> <hr> <p>Most popular and commonly referred online resources</p> <ul> <li><a href=Online-Material/Online-Material-for-Learning/ >Online Study Material</a></li> <li><a href=Online-Material/popular-resources/ >Popular Blogs</a></li> </ul> </details> </li> </ul> </div> <hr> <!-- <p align="center">
+</style> <h1 id=crack-data-science-interviews>Crack <strong>Data Science</strong> Interviews</h1> <div class="grid cards"> <ul> <li> <details class=interview-questions> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> Interview Questions</summary> <hr> <p>These are currently most commonly asked interview questions.</p> <p>Questions can be removed if they are no longer popular in interview circles and added as new question banks are released.</p> <ul> <li><a href=flashcards/ class=glowing-link>📇 Flashcards</a></li> <li><a href=Interview-Questions/data-structures-algorithms/ >DSA (Data Structures &amp; Algorithms)</a></li> <li><a href=Interview-Questions/System-design/ >System Design</a></li> <li><a href=Interview-Questions/Natural-Language-Processing/ >Natural Language Processing (NLP)</a></li> <li><a href=Interview-Questions/Probability/ >Probability</a></li> <li><a href=Interview-Questions/AB-testing/ >A/B Testing</a></li> <li><a href=Interview-Questions/SQL-Interview-Questions/ >SQL</a></li> <li><a href=Interview-Questions/Machine-Learning/ >ML-Algorithms</a></li> <li><a href=Interview-Questions/Python/ >Python</a></li> <li><a href=Interview-Questions/Pandas/ >Pandas</a></li> <li><a href=Interview-Questions/NumPy/ >NumPy</a></li> <li><a href=Interview-Questions/Scikit-Learn/ >Scikit-Learn</a></li> <li><a href=Interview-Questions/LangChain/ >LangChain</a></li> <li><a href=Interview-Questions/LangGraph/ >LangGraph</a></li> <li><a href=Interview-Questions/Forward-Deployed-Engineer/ >Forward Deployed Engineer (FDE)</a></li> <li><a href=Interview-Questions/Interview-Question-Resources/ >Interview Question Resources</a> - <strong>Community-curated sources for all topics</strong></li> </ul> </details> </li> <li> <details class=grokking> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> <strong>Grokking Interviews</strong></summary> <hr> <p>Free in-depth courses with worked examples, case studies and self-assessment</p> <ul> <li><a href=Grokking/ class=glowing-link>Overview and Shared Framework</a></li> <li><a href=Grokking/modern-system-design/ >Modern System Design</a></li> <li><a href=Grokking/ml-system-design/ >Machine Learning System Design</a></li> <li><a href=Grokking/generative-ai-system-design/ >Generative AI System Design</a></li> <li><a href=Grokking/mobile-system-design/ >Mobile System Design</a></li> <li><a href=Grokking/frontend-system-design/ >Frontend System Design</a></li> <li><a href=Grokking/product-architecture/ >Product Architecture</a></li> <li><a href=Grokking/system-design-fast-track/ >System Design Fast-Track (48 Hours)</a></li> </ul> </details> </li> <li> <details class=ml-algo> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> <strong>ML Algorithms</strong></summary> <hr> <p>From scratch implementation and documentation of all ML algorithms</p> <ul> <li><a href=Machine-Learning/ARIMA/ >ARIMA</a></li> <li><a href=Machine-Learning/Activation%20functions/ >Activation functions</a></li> <li><a href=Machine-Learning/Collaborative%20Filtering/ >Collaborative Filtering</a></li> <li><a href=Machine-Learning/Confusion%20Matrix/ >Confusion Matrix</a></li> <li><a href=Machine-Learning/DBSCAN/ >DBSCAN</a></li> <li><a href=Machine-Learning/Decision%20Trees/ >Decision Trees</a></li> <li><a href=Machine-Learning/Gradient%20Boosting/ >Gradient Boosting</a></li> <li><a href=Machine-Learning/K-means%20clustering/ >K-means clustering</a></li> <li><a href=Machine-Learning/Linear%20Regression/ >Linear Regression</a></li> <li><a href=Machine-Learning/Logistic%20Regression/ >Logistic Regression</a></li> <li><a href=Machine-Learning/Loss%20Function%20MAE%2C%20RMSE/ >Loss Function MAE, RMSE</a></li> <li><a href=Machine-Learning/Neural%20Networks/ >Neural Networks</a></li> <li><a href=Machine-Learning/Normal%20Distribution/ >Normal Distribution</a></li> <li><a href=Machine-Learning/Normalization%20Regularisation/ >Normalization Regularisation</a></li> <li><a href=Machine-Learning/Overfitting%2C%20Underfitting/ >Overfitting, Underfitting</a></li> <li><a href=Machine-Learning/PCA/ >PCA</a></li> <li><a href=Machine-Learning/Random%20Forest/ >Random Forest</a></li> <li><a href=Machine-Learning/Support%20Vector%20Machines/ >Support Vector Machines</a></li> <li><a href=Machine-Learning/Unbalanced%2C%20Skewed%20data/ >Unbalanced, Skewed data</a></li> <li><a href=Machine-Learning/kNN/ >kNN</a></li> </ul> </details> </li> <li> <details class=cheat-sheet> <summary><span class=twemoji><svg xmlns=http://www.w3.org/2000/svg viewbox="0 0 24 24"><path d="M13.22 19.03a.75.75 0 0 1 0-1.06L18.19 13H3.75a.75.75 0 0 1 0-1.5h14.44l-4.97-4.97a.749.749 0 0 1 .326-1.275.75.75 0 0 1 .734.215l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0"></path></svg></span> <strong>Cheat Sheets</strong></summary> <hr> <p>Distilled down important concepts for your quick reference</p> <ul> <li><a href=Cheat-Sheets/Django/ >Django</a></li> <li><a href=Cheat-Sheets/Flask/ >Flask</a></li> <li><a href=Cheat-Sheets/Hypothesis-Tests/ >Hypothesis-Tests</a></li> <li><a href=Cheat-Sheets/Keras/ >Keras</a></li> <li><a href=Cheat-Sheets/LangChain-LangGraph/ >LangChain-LangGraph</a></li> <li><a href=Cheat-Sheets/NumPy/ >NumPy</a></li> <li><a href=Cheat-Sheets/Pandas/ >Pandas</a></li> <li><a href=Cheat-Sheets/PySpark/ >PySpark</a></li> <li><a href=Cheat-Sheets/PyTorch/ >PyTorch</a></li> <li><a href=Cheat-Sheets/Python/ >Python</a></li> <li><a href=Cheat-Sheets/RegEx/ >RegEx</a></li> <li><a href=Cheat-Sheets/Sk-learn/ >Sk-learn</a></li> <li><a href=Cheat-Sheets/SQL/ >SQL</a></li> <li><a href=Cheat-Sheets/tensorflow/ >tensorflow</a></li> </ul> </details> </li> </ul> </div> <hr> <!-- <p align="center">
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