About

SuprSny is a Blogging platform that focuses on content related to Data Science, Artificial Intelligence (AI) & Machine Learning (ML), Banks, Finance, Cryptocurrencies, and General Topic.

About Me (the Blogger):

SUPRIA SONY
suprsny.com

I am a Data Science Professional with over 12 years of experience and hold a Masters Degree in Economics and an MBA in Finance. I have completed various Data Science certifications and actively writes blogs about Economics, Finance, and Data Science. My skills include Data Analysis with Python, SPSS, and Excel, as well as deploying Machine Learning Models like Regression, Classification, and Clustering. I also extract data using Python libraries and have experience in Survey Programming with SurveyToGo. I currently publish my blogs on suprsny.com and Quora (supriasonysspace.quora.com), and have contributed to Investment Shastra on MoneyWorks4Me.com.

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Links of my blogs on supriasonysspace.quora.com:

1. Which one should you focus on: Data Science or Machine Learning?


2. How does the Unsupervised Machine Learning Unlock the Hidden Patterns in Data?


3. What is Reinforcement Learning? How do Machines Learn through Trial and Error?


4. How does Reinforcement Learning relate to Nash Equilibrium in Game Theory


5. How Deep Learning is Powering the AI Revolution?


6. Does Deep Learning encompass the integration of supervised, unsupervised, and reinforcement learning, or is there a necessity for any additional learning types in its advancement?


7. What is Self-supervised learning and how is it different from Supervised Learning?


8. What is Semi-supervised learning?


9. Which approach yields superior outcomes: Self-supervised Learning or Semi-supervised Learning?


10. What is Transfer learning?


11. What is Meta-learning?


12. What is K-Means clustering and what are its applications?


13. What challenges arise in selecting the optimal number of clusters in unsupervised learning? How do we decide the number of clusters in K-Means clustering?


14. How is K-Means clustering applied in Image Compression? Which other techniques can do this task better than K-Means clustering?


15. Which technique is the most widely used technique for Image Compression?


16. How is K-Means clustering used in Document Classification? How widely is this method used for this task?


17. For which kinds of tasks K-Means is the most suitable method among all alternatives?


18. What is Hierarchical clustering and what is its application?


19. For Customer Segmentation, when should you use Hierarchical clustering and when K-Means clustering?


20. How does the choice of distance metrics affect the outcome of clustering algorithms?


21. What is AI-driven Sentiment Analysis? How do Machines Decode Human Emotions in Text?


22. Which method is most widely used for Document Classification?


23. What are the key differences between BERT and GPT?


24. How have the new versions of GPT and BERT pushed the boundaries of what language models can do?


25. What are the key Hyperparameters in Decision Trees?


26. When comparing Python and R, which programming language is more advantageous for data scientists?


27. What Python machine learning frameworks are essential to be familiar with?


28. What should you consider when choosing a Python IDE?


29. How Can Kaggle Datasets and Competitions Boost Your Data Science Journey?


30. What Are the Important Python Libraries for Data Scientists?


31. Which Is Better for Data Visualization: visualization tools like Tableau and Power BI or programming languages like R and Python?


32. What are the foundational assumptions of the Classical Linear Regression Model? Are these assumptions applicable to the Linear Regression Model used in Machine Learning as well?


33. What is the Bias-Variance Trade-off? What methods can be employed to attain a balance between Bias and Variance in Machine Learning?


34. What is K-Fold Cross Validation and How Does it Improve Model Evaluation?

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Links of my blogs on suprsny.com:

Artificial Intelligence (AI) and Machine Learning (ML)

1. The Transformative Power of Artificial Intelligence (AI) and Machine Learning (ML)


2. How Machine Learning is Revolutionizing the Healthcare Industry


3. How Machine Learning is Revolutionizing the Finance Industry


4. How AI and Machine Learning Are Changing the Transportation Sector


5. How AI and Machine Learning Are Transforming the Retail Sector


6. How AI and Machine Learning Are Transforming the Manufacturing Sector


7. How AI and Machine Learning Are Transforming the Marketing Industry


8. How AI and Machine Learning Are Transforming Our Everyday Routine


9. Narrow AI - the Specialized Artificial Intelligence: Key Aspects and Recent Advancements


10. General AI: How Close Are We to Achieving Human-Like Intelligence?


11. Safeguarding Human Intelligence: Essential Improvements for Thriving in an AI-Driven World


12. Supervised Machine Learning: How Machines Learn with Labeled Data


13. Unsupervised Machine Learning: How Machines Discover Insights Without Labels


14. How do machine learning models choose appealing ads for user segments?


15. Reinforcement Learning: Focus on Learning through interactions with environment


16. Neural Network: the core framework for Deep Learning Models


17. What is a Decision Tree?


18. TensorFlow: The Go-To Tool for AI and Machine Learning


19. Selecting the Best Free Python Data Science Environments


20. How Do Regression and Classification Differ in Supervised Machine Learning?


21. Estimating Fuel Efficiency using Linear Regression Model


22. Analysis of 'titanic' dataset to predict survivor traits using Logistic Regression Model

Cryptocurrencies

1. What are Cryptocurrencies, and what accounts for their increasing prominence?


2. What is Blockchain and how does it work?


3. What are Bitcoin and Altcoin?


4. What is a cryptocurrency wallet, and how can you secure it?


5. How Do Crypto Exchanges Facilitate Buying, Selling, and Trading Cryptocurrencies?


6. Utility Metrics for popular and emerging Cryptocurrencies


7. Approaches to Assessing the Value of Cryptocurrencies


8. How is Ethereum Revolutionizing the Future Beyond Digital Currency with Smart Contracts?


9. Is a special account required for trading cryptocurrencies, like a Demat account for stocks?


10. Investing in Cryptocurrencies: Risks and Rewards

Banking and Finance

1. SBI – Contribution in Financial Inclusion in India (2024)


2. Priority Sector Lending


3. EASE 7.0 of PSBs Reforms


4. JIO, LIC, and SBI - Among the Top 25 Strongest Brands Globally


5. Comparative Analysis of Business Segments of Top 3 Public Banks


6. Punjab National Bank – Focus on Retail, Agriculture and MSME


7. Bandhan Bank - Serving the underserved


8. Non-performing Assets


9. Capital Adequacy Ratio


10. Comparison of Net Interest Margins of Top 6 Banks in India


11. Sources of Funds of Banking Business


12. Comparison of Assets of Top 6 Banks in India


13. Analysis of Price-to-Book Ratio of Top 6 Banks in India


14. Comparison of Shareholding Patterns of Top 6 Banks in India


15. AU Small Finance Bank - The Success of 'Badlaav Hamse Hai' Ad Campaign


16. HDFC Bank - Journey from Bank to Financial Services Conglomerate

Company Snapshot

1. State Bank of India - Snapshot


2. Punjab National Bank - Snapshot


3. Bank of Baroda - Snapshot


4. HDFC Bank - Snapshot


5. ICICI Bank - Snapshot

General Topics

1. The Color Spectrum: How Colors Shape Emotions, Behaviors, and Perceptions


2. Safeguarding Human Intelligence: Essential Improvements for Thriving in an AI-Driven World


3. GST for Freelancers: A Complete Guide


4. Strive to stand out from the crowd within the group