Data Science & Machine Learning
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TOP 10 SQL Concepts for Job Interview

1. Aggregate Functions (SUM/AVG)
2. Group By and Order By
3. JOINs (Inner/Left/Right)
4. Union and Union All
5. Date and Time processing
6. String processing
7. Window Functions (Partition by)
8. Subquery
9. View and Index
10. Common Table Expression (CTE)


TOP 10 Statistics Concepts for Job Interview

1. Sampling
2. Experiments (A/B tests)
3. Descriptive Statistics
4. p-value
5. Probability Distributions
6. t-test
7. ANOVA
8. Correlation
9. Linear Regression
10. Logistics Regression


TOP 10 Python Concepts for Job Interview

1. Reading data from file/table
2. Writing data to file/table
3. Data Types
4. Function
5. Data Preprocessing (numpy/pandas)
6. Data Visualisation (Matplotlib/seaborn/bokeh)
7. Machine Learning (sklearn)
8. Deep Learning (Tensorflow/Keras/PyTorch)
9. Distributed Processing (PySpark)
10. Functional and Object Oriented Programming


#DataScienceWithDrAngshu #DataScience #Analytics #BigData #MachineLearning #ArtificialIntelligence #Python #SQL #Statistics #DataVisualisation #Experiments #Interview #Job
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Pattern Recognition and
Machine Learning [ Information Science and Statistics ]

Christopher M. Bishop
#python #machinelearning #statistics #information #ai #ml
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๐Ÿ”ฐ Machine Learning Roadmap for Beginners 2025
โ”œโ”€โ”€ ๐Ÿง  What is Machine Learning?
โ”œโ”€โ”€ ๐Ÿงช ML vs AI vs Deep Learning
โ”œโ”€โ”€ ๐Ÿ”ข Math Foundation (Linear Algebra, Calculus, Stats Basics)
โ”œโ”€โ”€ ๐Ÿ Python Libraries (NumPy, Pandas, Scikit-learn)
โ”œโ”€โ”€ ๐Ÿ“Š Data Preprocessing & Cleaning
โ”œโ”€โ”€ ๐Ÿ“‰ Feature Selection & Engineering
โ”œโ”€โ”€ ๐Ÿงญ Supervised Learning (Regression, Classification)
โ”œโ”€โ”€ ๐Ÿงฑ Unsupervised Learning (Clustering, Dimensionality Reduction)
โ”œโ”€โ”€ ๐Ÿ•น Model Evaluation (Confusion Matrix, ROC, AUC)
โ”œโ”€โ”€ โš™๏ธ Model Tuning (Hyperparameter Tuning, Grid Search)
โ”œโ”€โ”€ ๐Ÿงฐ Ensemble Methods (Bagging, Boosting, Random Forests)
โ”œโ”€โ”€ ๐Ÿ”ฎ Introduction to Neural Networks
โ”œโ”€โ”€ ๐Ÿ” Overfitting vs Underfitting
โ”œโ”€โ”€ ๐Ÿ“ˆ Model Deployment (Streamlit, Flask, FastAPI Basics)
โ”œโ”€โ”€ ๐Ÿงช ML Projects (Classification, Forecasting, Recommender)
โ”œโ”€โ”€ ๐Ÿ† ML Competitions (Kaggle, Hackathons)

Like for the detailed explanation โค๏ธ

#machinelearning
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๐—ฆ๐—ฏ๐—ฒ๐—ฟ๐Ÿฑ๐Ÿฌ๐Ÿฌ ๐—•๐—ฎ๐˜๐—ฐ๐—ต ๐Ÿณ โ€” ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—”๐—ฐ๐—ฐ๐—ฒ๐—น๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ ๐—ณ๐—ผ๐—ฟ ๐—”๐—œ & ๐——๐—ฒ๐—ฒ๐—ฝ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜๐˜‚๐—ฝ๐˜€ ๐Ÿš€

Ready to scale your startup beyond local market?

Who should apply:
โœ… Startups with MVP and early traction
โœ… DeepTech: GenAI, robotics, advanced materials, photonics, quantum computing
โœ… Applied AI for research, Earth remote sensing, autonomous transport
โœ… International founders exploring the Russian market

What you'll get:
๐Ÿ“ 12-week online program in English
๐Ÿ“ International mentors (Europe, US, Asia, Middle East)
๐Ÿ“ Access to investors & corporate customers
๐Ÿ“ Demo Day at Moscow Startup Summit (Fall 2026)

Results:
๐Ÿ“ˆ Revenue grows 4x on average, up to 1,000x for some teams
๐Ÿค 10,900+ contracts and pilots with corporations (6 seasons)

Program stages:
1๏ธโƒฃ Online bootcamp for 150 teams
2๏ธโƒฃ 25 best teams โ†’ intensive mentorship
3๏ธโƒฃ Demo Day presentation

Key details:
๐Ÿ“… Deadline: 10 April 2026
๐Ÿ’ฐ Participation: Free of charge
๐ŸŒ Format: Online
๐Ÿ’ฌ Language: English

๐—”๐—ฝ๐—ฝ๐—น๐˜† ๐—ก๐—ผ๐˜„ ๐Ÿ‘‡
https://sberbank-500.ru/

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React โค๏ธ for more startup opportunities!

#DataScience #MachineLearning #DeepTech #GenAI #Startup #Accelerator #AI
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