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Data Science News
Medium
2d
205
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How to Detect Liquidity Grabs Using Divergence Logic in Pine Script (Without Getting Faked Out…
- This article explains how to use divergence logic in Pine Script to detect liquidity grabs and avoid getting faked out.
- The author suggests combining level sweeps with divergence indicators to identify potential liquidity grab zones.
- By using tools such as RSI, OBV, MACD histogram, or volume, traders can find discrepancies between price and the chosen filter.
- The technique helps traders avoid being tricked by fake breakouts and instead observe others getting caught in liquidity grabs.
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Medium
2d
221
Humans are the smartest beings on earth but have you ever thought that human has biases that may…
- The Bayesian Technique is a method that can be used to address biases in decision-making.
- The technique involves considering the prior probability, likelihood, and total probability to make an informed decision.
- For example, when determining whether Steve is more likely to be a librarian or a farmer based on his personality traits, the base rate plays a significant role.
- Although people may have a bias toward labeling Steve as a librarian due to representativeness heuristic, the base rate of farmers outweighs the likelihood of librarians having those traits.
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Medium
2d
332
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Why .99 Still Wins Even with AI Setting the Prices
- .99 pricing has been popular for over a century due to its psychological impact on consumer behavior.
- The practice originated as a way to prevent theft in the early 1900s.
- Odd prices like $39 can feel more calculated and offer a perception of greater value than round numbers.
- Algorithms and AI models have learned from consumer behavior and still utilize .99 pricing for better conversion rates.
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Medium
2d
304
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How To Handle Conflict Between Managers As An Introvert
- Conflict can be uncomfortable but has value in bringing up tensions and serving as a catalyst for improvement.
- Handling conflict requires specific skills and perspective to turn it into an opportunity for growth.
- In conflicts between managers, ego and authority dynamics can complicate the resolution process.
- When mediating conflicts between managers, it's essential to establish trust and ensure respectful communication.
- Emotions are inevitable during conflicts, but managing them is crucial for effective conflict resolution.
- Two common types of conflicts to manage include differing opinions and personal attacks.
- Listening, asking open-ended questions, and remaining calm are key strategies for handling conflicts between managers.
- Resolving conflicts involves understanding each side's perspective and guiding them towards a mutually beneficial solution.
- Encouraging open communication, empathy, and collaboration is essential for resolving conflicts effectively.
- Patience, self-awareness, and active listening are valuable traits for introverts to mediate conflicts between managers.
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Analyticsindiamag
2d
79
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2am VC Fund to Back Early Stage Startups in Consumer Tech, AI, Fintech, and SaaS
- Venture capital firm 2am VC has launched its second fund to invest in 30 Indian startups across consumer tech, fintech, AI, food & beverage, and global SaaS.
- The firm will allocate 60% of the fund for initial investments and 40% for follow-on rounds.
- 2am VC has previously invested in 47 companies, including NEWME, Apna Mart, Bimaplan, and Karbon Card.
- The firm focuses on early-stage startups, mainly at the pre-seed to seed stage, and aims to support young and first-time Indian founders.
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Analyticsindiamag
2d
241
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Why Companies Are Moving Away from Next.js
- Several companies are reevaluating their use of Next.js due to recent troubles, including vulnerabilities and performance issues.
- Next.js, known for offering SEO benefits and a streamlined developer experience, is facing criticism for inefficiencies and slow rendering.
- Companies like Northflank saw significant improvements in performance when switching from Next.js to a custom-built React SSR solution.
- SEO advantages of Next.js have been overshadowed by slow render times, leading to a decline in SEO performance for some companies.
- Issues with Next.js governance and constant framework changes have left developers feeling frustrated and constantly refactoring applications.
- Developers have expressed concerns about Next.js's relationship with Vercel, suggesting a vendor lock-in strategy and limitations for self-hosting users.
- Technical issues like slow hot module reloading and prioritizing server-side rendering over client-side efficiency have contributed to developers seeking alternatives to Next.js.
- Despite criticisms, Next.js still has supporters who value its conventions, API routes, and TypeScript support for full-stack development.
- For teams deeply invested in the React ecosystem, Next.js may still be a viable choice; however, for those prioritizing performance and stability, alternatives are being considered.
- The industry sentiment towards Next.js seems to be shifting towards skepticism and criticism for its evolving structure and performance-related issues.
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Medium
2d
146
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Troubleshooting Virtual Environment and pip Install Issues in PowerShell with Visual Studio Code
- Troubleshooting virtual environment and pip install issues in PowerShell with Visual Studio Code.
- Occasionally, when installing a package, it may not be found by Visual Studio Code even after a successful installation.
- This issue is usually caused by the Python interpreter being used to run the code and the interpreter being used by pip during installation.
- Although the virtual environment may be active, pip might not be pointing to the correct interpreter.
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Medium
2d
273
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Artificial Intelligence Use in Smartphones Grows 250% in the Last Five Months
- According to the Samsung report, there are 200 million Galaxy smartphones in Latin America that integrate artificial intelligence.
- AI features have been used 1.157 billion times in the region.
- AI tools are available on mid-range smartphones like the Galaxy A56.
- Notable AI features include Circle to Search, Song Search, Best Face, Smart Object Eraser, and Filters.
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Banking Frontiers
2d
75
EC tests the prowess of DLT through a sandbox
- The European Commission has launched the European Blockchain Regulatory Sandbox to explore innovative use cases in Distributed Ledger Technologies (DLT).
- Started in 2023, the sandbox is funded by the Digital Europe Program and supports 20 projects annually, focusing on sectors like asset management, insurance, transportation, energy, and manufacturing.
- The key objectives of the sandbox include facilitating discussions between blockchain innovators and regulators, providing legal guidance, and developing best practices for blockchain adoption in various industries.
- It allows 20 selected projects per cohort to engage with national and EU regulators, with 3 cohorts planned for the initiative.
- The sandbox aims to promote cross-border collaboration within the EU's regulatory landscape and establish a dialogue between regulators, financial services supervisors, and corporate entities.
- Participating corporates and public entities are working on projects that have progressed beyond the proof-of-concept stage, with a focus on areas like CO2 emissions, cyber security, data sharing, and digital identities.
- The second cohort of the sandbox consists of 20 innovative projects, covering areas such as tokenization of assets, digital identity verification, and supply chain management.
- The sandbox is currently accepting applications for its third cohort, with projects focusing on decentralized finance (DeFi), healthcare data sharing, and smart contracts for legal agreements.
- Key outcomes of the sandbox include facilitating regulatory dialogue, providing legal clarity for emerging blockchain use cases, enhancing regulators' understanding of blockchain technology, and fostering knowledge sharing among blockchain innovators.
- Overall, the sandbox has successfully facilitated discussions between regulators and innovators, encouraged testing of blockchain applications, and offered insights into how existing laws apply to blockchain projects.
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Nycdatascience
2d
158
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How AI is Revolutionizing Healthcare: A Data Scientist’s Perspective
- The integration of Artificial Intelligence (AI) in healthcare is transforming the industry, enhancing diagnosis accuracy, improving treatment plans, and streamlining operational efficiency.
- AI-powered diagnostic tools have significantly improved the accuracy and speed of disease detection in radiology, pathology, ophthalmology, and dermatology.
- AI contributes significantly to personalized medicine, analyzing genomic data, lifestyle choices, and medical history to predict patient responses to specific treatments in areas like oncology, cardiology, and neurology.
- AI optimizes healthcare operations, leading to reduced costs and improved patient care through administrative automation, predictive maintenance, and supply chain management.
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Medium
2d
122
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Egopoetic Technology; Ad-Hoc Algorithms and The Alt Right Pipeline
- The UK Netflix mini series 'Adolescence' has sparked discussions about the 'manosphere' and incel culture re-entering mainstream conversations.
- Online spaces like those explored in Laura Bates' book 'Men who hate Women' preach self-valorization but breed extreme insecurity.
- Andrew Tate, a figure in incel culture, exemplifies the creation of self-involved yet insecure young boys through online platforms.
- Algorithms play a role in guiding individuals towards extreme ideologies through ad-hoc group classification.
- Ad-hoc algorithms lack nuance and individual agency, grouping users based on perceived similarities without common intentions.
- Individuals may be unaware of belonging to ad-hoc groups, leading to indoctrination without self-awareness.
- The use of algorithms to categorize individuals in the manosphere for targeted advertising raises concerns about privacy and manipulation.
- Digital capitalism and algorithm optimization contribute to the proliferation of harmful content targeting vulnerable audiences.
- The integration of AI with surveillance systems raises concerns about oversimplification and lack of human discretion in decision-making.
- Data analytics advancements call for protections of privacy interests of ad-hoc groups formed through algorithmic classification.
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Towards Data Science
3d
87
Data Science: From School to Work, Part III
- Error handling is a critical part of building robust applications, preventing crashes and inconsistent data.
- Proper error handling in Python involves try-except blocks, raising exceptions, and using the finally statement for cleanup actions.
- Specific exceptions like ZeroDivisionError, KeyError, IndexError, TypeError, and FileNotFoundError should be caught and handled.
- Custom errors can also be defined and raised in Python code.
- The finally block executes cleanup actions regardless of errors occurring or not.
- Best practices for error handling include catching specific exceptions, providing explicit messages, avoiding silent failures, and using else and finally blocks.
- Logs are essential for tracking events during program execution, debugging, and monitoring application health.
- The loguru package in Python simplifies logging with different levels like DEBUG, INFO, ERROR, and CRITICAL, allowing for better message formatting.
- New log levels can be defined, and configurations like sink, level, format, filter, colorize, and serialize can be customized in loguru.
- Adding context data like user IDs to logs and using child loggers in loguru can help in troubleshooting complex applications.
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Medium
3d
199
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Everything You Need To Know on LLMs : Brick by Brick
- LLMs (Large Language Models) are often treated as black boxes by most people.
- This article aims to provide a breakdown of LLMs layer by layer for better understanding and examination of machine learning models.
- Tokenization is the process of splitting large text into smaller text pieces called tokens, which can be as small as a character or as large as a word.
- Tokens can be words, subwords, or even characters depending on the model's design.
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Medium
3d
230
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Boosting Data Pipeline Reliability with AI and Minimal Costs
- The article provides a practical guide and code for implementing AI to enhance data pipeline reliability.
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Hackernoon
3d
27
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Embeddings 101: Unlocking Semantic Relationships in Text
- Embeddings revolutionized how machines understand language by addressing limitations in previous methods like one-hot encoding, bag-of-words, N-grams, and TF-IDF.
- Early embedding models like Word2Vec captured semantic relationships by training neural networks to predict words based on context or context based on words.
- Models like Word2Vec and GloVe offered single vectors for words, but contextual embeddings like BERT and GPT provided dynamic word representations based on context.
- Embeddings are numerical representations in a continuous vector space that capture semantic relationships, allowing machines to process language.
- Dimensions in embedding vectors represent abstract concepts that emerge during training.
- Embeddings enable semantic similarity, preserve context, allow mathematical operations, and work efficiently at scale.
- Dense vector representations in embeddings use fewer dimensions for efficiency and richer semantic content.
- Embeddings are built on distributional semantics principle and have remarkable mathematical properties for analogical reasoning.
- Transfer learning with pre-trained embeddings like BERT reduces data requirements for new applications.
- Methods like Mean Pooling, Max Pooling, Weighted Mean Pooling, and Last Token Pooling offer different approaches to create embeddings for various tasks.
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