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Data Science News
Dev
2w
387
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2140. Solving Questions With Brainpower
- Given a 0-indexed 2D integer array 'questions' representing an exam where each question has points and brainpower constraints.
- The task is to maximize points by solving questions considering brainpower limitations.
- Dynamic Programming is suggested to decide the most optimal option for each question.
- Solution involves DP array to track maximum points starting from each question.
- For each question, two choices exist: solve with constraints or skip to the next.
- Reverse iteration helps in considering each question's impact on future questions.
- The algorithm efficiently determines the maximum points earned from solving exam questions.
- Initialization of DP array and iterating from last question aids in optimal point calculation.
- The approach computes the solution in O(n) time and space complexity for large input sizes.
- Dynamic Programming is a powerful technique for optimizing decision-making processes in various scenarios.
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Towards Data Science
2w
367
A Simple Implementation of the Attention Mechanism from Scratch
- The Attention Mechanism is crucial in tasks like Machine Translation to focus on important words for prediction.
- It helped RNNs mitigate the vanishing gradient problem and capture long-range dependencies among words.
- Self-attention in Transformers provides information on the correlation between words in the same sequence.
- It generates attention weights for each token based on other tokens in the sequence.
- By multiplying query and key vectors and applying softmax, attention weights are obtained.
- Multi-head Self-Attention in Transformers uses multiple sets of matrices to capture diverse relationships among tokens.
- The dense vectors from each head are concatenated and linearly transformed to get the final output.
- The implementation involves generating query, key, and value vectors for each token and calculating attention scores.
- Softmax is applied to get attention weights, and the final context-aware vector is computed for each token.
- A multi-head attention mechanism with separate weight matrices for each head is used to improve relationship capture.
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Towards Data Science
2w
197
Create Your Supply Chain Analytics Portfolio to Land Your Dream Job
- Supply Chain Analytics is crucial for resilient operations in today's volatile supply chain landscape, driven by factors like climate disruptions and geopolitical shifts.
- The article discusses building a supply chain analytics portfolio with actual projects, presenting insights from the author's nine years of industry experience.
- The Supply Chain Analytics Cheat Sheet provides tools, methodologies, and case studies to extract insights and optimize supply chain solutions.
- It covers topics like data analytics for business strategy, logistics operations optimization, supply chain flow optimization, and sustainability.
- Readers are guided on how to leverage analytics to boost profitability, optimize supply chain operations, and support sustainability initiatives.
- The article suggests starting with a simple project, adding business value, refactoring code, and improving user interface to build a strong analytics portfolio.
- By showcasing practical applications of analytics in supply chains, aspiring data scientists can demonstrate their skills and potentially land job opportunities in the field.
- The author also emphasizes the importance of understanding business needs, packaging code for deployment, and enhancing insights for effective analytics solutions.
- Overall, leveraging supply chain analytics through portfolio projects can showcase expertise and creativity in applying data-driven solutions to real-world challenges.
- The article encourages readers to engage with the author's content, use the provided resources to enhance their skills, and contribute to the analytics community.
- Building a strong portfolio in supply chain analytics can open doors to exciting career opportunities and enable individuals to make a tangible impact in the industry.
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Towards Data Science
2w
34
Understanding the Tech Stack Behind Generative AI
- The article explores the technology ecosystem around generative AI and Large Language Models (LLMs).
- Foundation models are pre-trained AI models that are versatile and can perform various tasks ranging from text generation to music composition.
- Key aspects of foundation models include pre-training, multitask capability, and transferability through fine-tuning or Retrieval Augmented Generation (RAG).
- Major players in AI like OpenAI, Anthropic, Google, Meta, Mistral, and DeepSeek have released foundation models with varying strengths and licensing conditions.
- Multimodal models can process and generate different types of data simultaneously, such as text, images, audio, and video.
- Infrastructure and compute power, including GPUs, TPUs, ML frameworks like PyTorch and TensorFlow, and serverless AI architectures, play a vital role in training generative AI models.
- AI applications frameworks like LangChain, LlamaIndex, and Ollama help integrate foundation models into specific applications efficiently.
- Vector databases are used to store and search semantic information in the context of LLMs, enabling fast similarity searches for contextual information.
- Programming languages like Python, Rust, C++, and Julia are important for developing generative AI, with Python being the primary language for AI applications.
- The social layer of AI focusing on explainability, fairness, and governance addresses important ethical considerations in the use of generative AI.
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Medium
2w
65
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Best apps for the month — April 2025
- Superlist is an iOS app that offers efficient task management and to-do list features.
- Quizlet is an iOS app focused on flashcard-based learning, offering a large database of existing flashcard sets and various types of tests.
- Pushbullet is a popular Android app for communicating between devices, enabling file sharing, notification mirroring, and messaging.
- Moises is a creative app that allows users to extract or eliminate vocals and instruments from any song, offering unique possibilities for musicians and music enthusiasts.
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Hackernoon
2w
152
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Navigating MySQL data types: date and time
- MySQL provides various data types for storing time data, including DATETIME and TIMESTAMP.
- The DATETIME data type stores date and time in the format YYYY-MM-DD HH:MM:SS and does not store or convert time zone data.
- The TIMESTAMP data type is internally represented as a Unix epoch and automatically adapts to the time zone of the server.
- There are some unexpected features to be aware of, such as using NULL to initialize TIMESTAMP columns and dealing with zero dates.
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Medium
2w
117
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Dataset Definition, Types, Benefits, and Use Cases
- Before the rise of machine learning (ML), data science focused on traditional statistical analysis, manual data handling, data visualization, and predictive analytics without ML.
- Data science before machine learning primarily used predefined models and rules to derive insights.
- Structured datasets are well-organized and stored in a table-like format, typically in relational databases or spreadsheets.
- Unstructured data refers to datasets that aren't stored in a structured format, including audio and video datasets.
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Medium
2w
39
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Prompt Engineering: Unlocking AI’s Potential with Chain-of-Thought and Few-Shot Learning
- Advanced prompt engineering for language models enables communication with a digital helper that thinks through problems like a human.
- The Chain-of-Thought (CoT) technique breaks down complex puzzles into manageable parts, enabling the models to think step-by-step and achieve new levels of understanding and clarity.
- By using CoT, language models learn to tackle math problems with logic, reducing mistakes and providing easy-to-understand explanations.
- Few-shot prompting enables machines to make informed predictions by learning from just a few examples, similar to skilled baristas pouring tea with a clear understanding of how much to pour.
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Medium
2w
417
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Decoding Data Products: More Than Just Data
- A data product is a complete, ready-to-use package built from data that delivers specific value to a defined group of users.
- Similar to buying cereal in a box, a data product includes important information and is designed for easy consumption.
- A data product typically includes data, algorithms, documentation, user interfaces, and customer support.
- It has a designated owner responsible for its quality, lifecycle, and value delivery, applying product management principles.
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Medium
2w
356
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More Liquidity, More Earnings: How SettleTON Optimizes Your Crypto Strategy
- SettleTON’s re-farming contract, powered by STONfi v2, automates liquidity management.
- Vaults & Indexes simplify complex strategies, eliminating the need for active liquidity adjustments.
- Automated re-farming ensures productive funds without idle assets.
- SettleTON's integration of smart liquidity management provides better capital efficiency and higher returns for liquidity providers.
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VentureBeat
2w
339
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Runway Gen-4 solves AI video’s biggest problem: character consistency across scenes
- Runway AI Inc. launched its most advanced AI video generation model called Gen-4, which focuses on character and scene consistency across multiple shots.
- Gen-4 aims to address the challenge of maintaining visual elements such as character faces and background elements across scenes in AI-generated videos.
- The new model by Runway allows users to create five and ten-second clips at 720p resolution.
- Runway's Gen-4 creates a persistent memory of visual elements to render consistent outputs from different angles, enhancing storytelling capabilities in videos.
- The company showcases the capabilities of Gen-4 through short films like 'New York is a Zoo' and 'The Retrieval.'
- Runway's strategic approach focuses on building a complete digital production pipeline, catering to the needs of filmmakers for performance, coverage, and visual continuity.
- The company is raising significant funding, aiming for $300 million in annualized revenue, and has partnerships with Hollywood studios like Lionsgate.
- While providing opportunities for independent creators, AI video generation technology like Gen-4 raises concerns about potential job loss in the film industry due to automation.
- Legal issues surround AI training data sources and copyright infringement allegations against companies like Runway, leading to debates on fair use and style mimicry.
- The technology opens doors for creative applications in marketing, education, and corporate communications, offering both opportunities and disruptions in the filmmaking landscape.
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Towards Data Science
2w
121
My Learning to Be Hired Again After a Year… Part 2
- After a year of unemployment, the author reflects on finding meaning and identity outside of a job title or company name.
- Deciding to pivot to machine learning engineering, the author sought advice from friends who had made a similar career move.
- Despite the competitive job market, the author chose to try for machine learning engineer positions even at entry level.
- By focusing on self-improvement and showing value in interviews, the author gained three job offers for senior MLE roles.
- The author emphasizes the importance of not begging for jobs but rather selling oneself effectively.
- Through mock interviews and practice, the author improved behavioral interview skills and changed their mindset towards job interviews.
- Struggling with nervousness and judgment during interviews, the author learned to pause, breathe, and refocus to regain control.
- Utilizing the Mnookin Two-Pager exercise helped the author clarify job preferences and goals, leading to a better job fit at Disney.
- Writing as a way to reflect, the author invites readers to follow their posts on TDS and subscribe to their newsletter for more insights and humor.
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Analyticsindiamag
2w
117
Image Credit: Analyticsindiamag
HCLTech Joins Samsung Advanced Foundry Ecosystem as Design Solution Partner
- HCLTech selected as a Design Solution Partner (DSP) by Samsung Advanced Foundry Ecosystem (SAFE) program.
- Partnership aims to accelerate semiconductor innovation using HCLTech's expertise in engineering and R&D services and Samsung's cutting-edge process technologies.
- HCLTech to offer ASIC design services for customers utilizing Samsung's advanced manufacturing processes under SAFE-DSP program, reducing time-to-market for new silicon technologies.
- Partnership grants HCLTech access to MPW programs and training in advanced semiconductor technologies from Samsung.
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Medium
2w
317
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I Just Discovered A Dirty Little Secret About ChatGPT
- ChatGPT has a hidden data control option in the settings.
- The author discovered this hidden feature by exploring the ChatGPT settings.
- The data control option allows users to have control over their data.
- The feature was overlooked by the author and is considered a dirty little secret.
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Analyticsindiamag
2w
337
Image Credit: Analyticsindiamag
Amazon Unveils Nova Act, an AI Agent to Control Web Browsers
- Amazon has launched the Nova Act SDK, an AI agent trained to perform tasks within a web browser.
- Nova Act SDK automates workflows by breaking down complex tasks into smaller commands and allows developers to integrate API calls.
- Users with an Amazon account can access nova.amazon.com to explore Nova models and test the Nova Act SDK.
- Nova Act is Amazon's AGI lab's first product and competes with OpenAI's Operator and Anthropic's Computer Use agents.
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