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
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
๐2
Pattern Recognition and
Machine Learning [ Information Science and Statistics ]
Christopher M. Bishop
#python #machinelearning #statistics #information #ai #ml
Machine Learning [ Information Science and Statistics ]
Christopher M. Bishop
#python #machinelearning #statistics #information #ai #ml
๐2
๐ฐ Machine Learning Roadmap for Beginners 2025
โโโ ๐ง What is Machine Learning?
โโโ ๐งช ML vs AI vs Deep Learning
โโโ ๐ข Math Foundation (Linear Algebra, Calculus, Stats Basics)
โโโ ๐ Python Libraries (NumPy, Pandas, Scikit-learn)
โโโ ๐ Data Preprocessing & Cleaning
โโโ ๐ Feature Selection & Engineering
โโโ ๐งญ Supervised Learning (Regression, Classification)
โโโ ๐งฑ Unsupervised Learning (Clustering, Dimensionality Reduction)
โโโ ๐น Model Evaluation (Confusion Matrix, ROC, AUC)
โโโ โ๏ธ Model Tuning (Hyperparameter Tuning, Grid Search)
โโโ ๐งฐ Ensemble Methods (Bagging, Boosting, Random Forests)
โโโ ๐ฎ Introduction to Neural Networks
โโโ ๐ Overfitting vs Underfitting
โโโ ๐ Model Deployment (Streamlit, Flask, FastAPI Basics)
โโโ ๐งช ML Projects (Classification, Forecasting, Recommender)
โโโ ๐ ML Competitions (Kaggle, Hackathons)
Like for the detailed explanation โค๏ธ
#machinelearning
โโโ ๐ง What is Machine Learning?
โโโ ๐งช ML vs AI vs Deep Learning
โโโ ๐ข Math Foundation (Linear Algebra, Calculus, Stats Basics)
โโโ ๐ Python Libraries (NumPy, Pandas, Scikit-learn)
โโโ ๐ Data Preprocessing & Cleaning
โโโ ๐ Feature Selection & Engineering
โโโ ๐งญ Supervised Learning (Regression, Classification)
โโโ ๐งฑ Unsupervised Learning (Clustering, Dimensionality Reduction)
โโโ ๐น Model Evaluation (Confusion Matrix, ROC, AUC)
โโโ โ๏ธ Model Tuning (Hyperparameter Tuning, Grid Search)
โโโ ๐งฐ Ensemble Methods (Bagging, Boosting, Random Forests)
โโโ ๐ฎ Introduction to Neural Networks
โโโ ๐ Overfitting vs Underfitting
โโโ ๐ Model Deployment (Streamlit, Flask, FastAPI Basics)
โโโ ๐งช ML Projects (Classification, Forecasting, Recommender)
โโโ ๐ ML Competitions (Kaggle, Hackathons)
Like for the detailed explanation โค๏ธ
#machinelearning
โค7๐2
๐ฆ๐ฏ๐ฒ๐ฟ๐ฑ๐ฌ๐ฌ ๐๐ฎ๐๐ฐ๐ต ๐ณ โ ๐๐ฟ๐ฒ๐ฒ ๐๐ฐ๐ฐ๐ฒ๐น๐ฒ๐ฟ๐ฎ๐๐ผ๐ฟ ๐ณ๐ผ๐ฟ ๐๐ & ๐๐ฒ๐ฒ๐ฝ๐ง๐ฒ๐ฐ๐ต ๐ฆ๐๐ฎ๐ฟ๐๐๐ฝ๐ ๐
Ready to scale your startup beyond local market?
Who should apply:
โ Startups with MVP and early traction
โ DeepTech: GenAI, robotics, advanced materials, photonics, quantum computing
โ Applied AI for research, Earth remote sensing, autonomous transport
โ International founders exploring the Russian market
What you'll get:
๐ 12-week online program in English
๐ International mentors (Europe, US, Asia, Middle East)
๐ Access to investors & corporate customers
๐ Demo Day at Moscow Startup Summit (Fall 2026)
Results:
๐ Revenue grows 4x on average, up to 1,000x for some teams
๐ค 10,900+ contracts and pilots with corporations (6 seasons)
Program stages:
1๏ธโฃ Online bootcamp for 150 teams
2๏ธโฃ 25 best teams โ intensive mentorship
3๏ธโฃ Demo Day presentation
Key details:
๐ Deadline: 10 April 2026
๐ฐ Participation: Free of charge
๐ Format: Online
๐ฌ Language: English
๐๐ฝ๐ฝ๐น๐ ๐ก๐ผ๐ ๐
https://sberbank-500.ru/
๐ฅ Don't wait. Scale your startup with Sber500.
React โค๏ธ for more startup opportunities!
#DataScience #MachineLearning #DeepTech #GenAI #Startup #Accelerator #AI
Ready to scale your startup beyond local market?
Who should apply:
โ Startups with MVP and early traction
โ DeepTech: GenAI, robotics, advanced materials, photonics, quantum computing
โ Applied AI for research, Earth remote sensing, autonomous transport
โ International founders exploring the Russian market
What you'll get:
๐ 12-week online program in English
๐ International mentors (Europe, US, Asia, Middle East)
๐ Access to investors & corporate customers
๐ Demo Day at Moscow Startup Summit (Fall 2026)
Results:
๐ Revenue grows 4x on average, up to 1,000x for some teams
๐ค 10,900+ contracts and pilots with corporations (6 seasons)
Program stages:
1๏ธโฃ Online bootcamp for 150 teams
2๏ธโฃ 25 best teams โ intensive mentorship
3๏ธโฃ Demo Day presentation
Key details:
๐ Deadline: 10 April 2026
๐ฐ Participation: Free of charge
๐ Format: Online
๐ฌ Language: English
๐๐ฝ๐ฝ๐น๐ ๐ก๐ผ๐ ๐
https://sberbank-500.ru/
๐ฅ Don't wait. Scale your startup with Sber500.
React โค๏ธ for more startup opportunities!
#DataScience #MachineLearning #DeepTech #GenAI #Startup #Accelerator #AI
โค7๐ฅ1