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* Machine Learning

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Important questions to ace your machine learning interview with an approach to answer:

1. Machine Learning Project Lifecycle:
   - Define the problem
   - Gather and preprocess data
   - Choose a model and train it
   - Evaluate model performance
   - Tune and optimize the model
   - Deploy and maintain the model

2. Supervised vs Unsupervised Learning:
   - Supervised Learning: Uses labeled data for training (e.g., predicting house prices from features).
   - Unsupervised Learning: Uses unlabeled data to find patterns or groupings (e.g., clustering customer segments).

3. Evaluation Metrics for Regression:
   - Mean Absolute Error (MAE)
   - Mean Squared Error (MSE)
   - Root Mean Squared Error (RMSE)
   - R-squared (coefficient of determination)

4. Overfitting and Prevention:
   - Overfitting: Model learns the noise instead of the underlying pattern.
   - Prevention: Use simpler models, cross-validation, regularization.

5. Bias-Variance Tradeoff:
   - Balancing error due to bias (underfitting) and variance (overfitting) to find an optimal model complexity.

6. Cross-Validation:
   - Technique to assess model performance by splitting data into multiple subsets for training and validation.

7. Feature Selection Techniques:
   - Filter methods (e.g., correlation analysis)
   - Wrapper methods (e.g., recursive feature elimination)
   - Embedded methods (e.g., Lasso regularization)

8. Assumptions of Linear Regression:
   - Linearity
   - Independence of errors
   - Homoscedasticity (constant variance)
   - No multicollinearity

9. Regularization in Linear Models:
   - Adds a penalty term to the loss function to prevent overfitting by shrinking coefficients.

10. Classification vs Regression:
    - Classification: Predicts a categorical outcome (e.g., class labels).
    - Regression: Predicts a continuous numerical outcome (e.g., house price).

11. Dimensionality Reduction Algorithms:
    - Principal Component Analysis (PCA)
    - t-Distributed Stochastic Neighbor Embedding (t-SNE)

12. Decision Tree:
    - Tree-like model where internal nodes represent features, branches represent decisions, and leaf nodes represent outcomes.

13. Ensemble Methods:
    - Combine predictions from multiple models to improve accuracy (e.g., Random Forest, Gradient Boosting).

14. Handling Missing or Corrupted Data:
    - Imputation (e.g., mean substitution)
    - Removing rows or columns with missing data
    - Using algorithms robust to missing values

15. Kernels in Support Vector Machines (SVM):
    - Linear kernel
    - Polynomial kernel
    - Radial Basis Function (RBF) kernel

Data Science Interview Resources
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Currently it's for working professionals only, I will update once we launch it for students as well
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Programming Languages & What Theyโ€™re Really Good At

Python ๐Ÿ โ€“ Data analysis, automation, AI/ML

Java โ˜• โ€“ Android apps, enterprise software

JavaScript โšก โ€“ Interactive websites, full-stack apps

C++ โš™๏ธ โ€“ Game development, system-level software

C# ๐ŸŽฎ โ€“ Unity games, Windows apps

R ๐Ÿ“Š โ€“ Statistical analysis, data visualization

Go ๐Ÿš€ โ€“ Fast APIs, cloud-native apps

PHP ๐Ÿ˜ โ€“ WordPress, backend for websites

Swift ๐ŸŽ โ€“ iOS/macOS apps

Kotlin ๐Ÿ“ฑ โ€“ Modern Android development
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Top 10 Python Project Ideas ๐Ÿ’ก
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Resources for Tech Interviews ๐Ÿ‘†
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List of AI Project Ideas ๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป๐Ÿค– -

Beginner Projects

๐Ÿ”น Sentiment Analyzer
๐Ÿ”น Image Classifier
๐Ÿ”น Spam Detection System
๐Ÿ”น Face Detection
๐Ÿ”น Chatbot (Rule-based)
๐Ÿ”น Movie Recommendation System
๐Ÿ”น Handwritten Digit Recognition
๐Ÿ”น Speech-to-Text Converter
๐Ÿ”น AI-Powered Calculator
๐Ÿ”น AI Hangman Game

Intermediate Projects

๐Ÿ”ธ AI Virtual Assistant
๐Ÿ”ธ Fake News Detector
๐Ÿ”ธ Music Genre Classification
๐Ÿ”ธ AI Resume Screener
๐Ÿ”ธ Style Transfer App
๐Ÿ”ธ Real-Time Object Detection
๐Ÿ”ธ Chatbot with Memory
๐Ÿ”ธ Autocorrect Tool
๐Ÿ”ธ Face Recognition Attendance System
๐Ÿ”ธ AI Sudoku Solver

Advanced Projects

๐Ÿ”บ AI Stock Predictor
๐Ÿ”บ AI Writer (GPT-based)
๐Ÿ”บ AI-powered Resume Builder
๐Ÿ”บ Deepfake Generator
๐Ÿ”บ AI Lawyer Assistant
๐Ÿ”บ AI-Powered Medical Diagnosis
๐Ÿ”บ AI-based Game Bot
๐Ÿ”บ Custom Voice Cloning
๐Ÿ”บ Multi-modal AI App
๐Ÿ”บ AI Research Paper Summarizer

Join for more: https://t.me/machinelearning_deeplearning
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List of most asked Programming Interview Questions.

Arrays

- How is an array sorted using quicksort?
- How do you reverse an array?
- How do you remove duplicates from an array?
- How do you find the 2nd largest number in an unsorted integer array?

Linked Lists

- How do you find the length of a linked list?
- How do you reverse a linked list?
- How do you find the third node from the end?
- How are duplicate nodes removed in an unsorted linked list?

Strings

- How do you check if a string contains only digits?
- How can a given string be reversed?
- How do you find the first non-repeated character?
- How do you find duplicate characters in strings?

Binary Trees

- How are all leaves of a binary tree printed?
- How do you check if a tree is a binary search tree?
- How is a binary search tree implemented?
- Find the lowest common ancestor in a binary tree?

Graph

- How to detect a cycle in a directed graph?
- How to detect a cycle in an undirected graph?
- Find the total number of strongly connected components?
- Find whether a path exists between two nodes of a graph?
- Find the minimum number of swaps required to sort an array.

Dynamic Programming

1. Find the longest common subsequence?
2. Find the longest common substring?
3. Coin change problem?
4. Box stacking problem?
5. Count the number of ways to cover a distance?

React with โค๏ธ for the detailed answers
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List of Frontend Project Ideas ๐Ÿ’ก๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป

Beginner Projects

๐Ÿ”น Personal Portfolio Website
๐Ÿ”น Responsive Landing Page
๐Ÿ”น Simple Calculator
๐Ÿ”น To-Do List App
๐Ÿ”น Weather App

Intermediate Projects

๐Ÿ”ธ Blog Website
๐Ÿ”ธ E-commerce Product Page
๐Ÿ”ธ Recipe Finder App
๐Ÿ”ธ Interactive Chat App
๐Ÿ”ธ Music Player

Advanced Projects

๐Ÿ”บ Social Media Dashboard
๐Ÿ”บ Real-time Chat Application
๐Ÿ”บ Multi-page E-commerce Website
๐Ÿ”บ Dynamic Data Visualization Dashboard

React โค๏ธ for more
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Tips for solving leetcode codings interview problems

If input array is sorted then
- Binary search
- Two pointers

If asked for all permutations/subsets then
- Backtracking

If given a tree then
- DFS
- BFS

If given a graph then
- DFS
- BFS

If given a linked list then
- Two pointers

If recursion is banned then
- Stack

If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer

If asked for maximum/minimum subarray/subset/options then
- Dynamic programming

If asked for top/least K items then
- Heap

If asked for common strings then
- Map
- Trie

Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
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Random Module in Python ๐Ÿ‘†
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