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Data Science News
Medium
7d
107
Image Credit: Medium
10 Developer Habits That Made Me a 6-Figure Coder
- Developers should use meaningful variable and function names, write docstrings for every function, keep functions small and single-responsibility, and avoid unnecessary complexity.
- Automation is crucial in saving time and improving efficiency in development tasks.
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Towards Data Science
7d
56
Automate Supply Chain Analytics Workflows with AI Agents using n8n
- The article discusses the use of n8n, a low-code platform, to automate supply chain analytics workflows and build AI agents.
- The author initially explored frameworks like LangChain and LangGraph before discovering the power of n8n.
- n8n is an open-source workflow automation tool that allows easy connection between apps, APIs, and AI model frameworks.
- The example provided in the article demonstrates the ease of replicating an AI agent built with Python using n8n with minimal code.
- The AI Supply Chain Control Tower workflow in n8n includes sub-workflows, chat interfaces, AI agents, and SQL querying.
- The process is smooth and requires limited configuration, making it accessible even for individuals with limited Python skills.
- The article highlights that while n8n simplifies automation, Python is not obsolete and can still be valuable for supply chain analytics.
- n8n offers easy connectivity to various services and the flexibility to enhance analytics products by adding additional connections.
- The author, Samir Saci, is a Supply Chain Engineer who focuses on using data analytics to enhance logistics operations and reduce costs.
- For consulting or advice on analytics and sustainable Supply Chain transformation, the author can be contacted via Logigreen Consulting.
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Medium
7d
124
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Choosing ML Algorithms: Navigating Complex Data with Confidence
- Choosing the right machine learning algorithm can be a complex journey.
- A project requiring a predictive model led to a transformation in the author's approach.
- The data was complex, messy, and required an algorithm that could handle its intricacies.
- The author realized that understanding and making sense of the data was as important as the prediction itself.
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Towards Data Science
7d
311
AI Agents from Zero to Hero — Part 2
- AI Agents are autonomous programs that perform tasks, make decisions, and communicate with others.
- Agents organize tasks into a logical progression and adapt their strategies in dynamic environments.
- Iterations involve repeating actions with slight changes or improvements in each cycle to refine output or reach optimal solutions.
- Chains are sequences of linked actions where each step depends on the previous one, forming a continuous flow of operations.
- The tutorial demonstrates using iterations and chains for AI Agents, with Python code examples for practical application.
- Tools like YahooFinance APIs and matplotlib are utilized to download and visualize financial data.
- The article introduces a function to process model responses and handle the usage of tools by the Agent.
- By incorporating iterations, the Agent can retry actions multiple times to solve problems and adapt.
- Chains allow for a linear sequence of actions, with outputs of one step used as inputs for subsequent steps, enhancing problem-solving capabilities.
- The structured approach using iterations and chains enhances the reliability of AI Agents, enabling developers to create customized solutions for various scenarios.
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Towards Data Science
7d
262
Uncertainty Quantification in Machine Learning with an Easy Python Interface
- Uncertainty quantification in machine learning (ML) models is crucial for understanding the precision of predictions, especially in real-world applications.
- ML Uncertainty is a Python package that offers an intuitive interface to estimate uncertainties in ML predictions and model parameters using powerful mathematical methods.
- The package supports linear regression, LASSO regression, ridge regression, elastic net, regression splines, and non-linear regression.
- ML Uncertainty allows for uncertainty estimation in random forests by leveraging bootstrapping techniques to estimate prediction intervals.
- The ErrorPropagation class in ML Uncertainty computes uncertainty in response variables due to uncertainties in input variables and model parameters.
- ML Uncertainty distinguishes itself by enabling uncertainty propagation and catering to various models beyond linear regression.
- The package optimizes computational efficiency by separating model training from uncertainty quantification to offer reliable estimates.
- Future work involves expanding ML Uncertainty to other ML frameworks like PyTorch and TensorFlow, adding support for more models, and improving documentation.
- ML Uncertainty aims to enhance the reliability and interpretability of machine learning models by providing efficient uncertainty quantification tools.
- Contributions from the open-source community are encouraged to enhance the capabilities and applicability of the ML Uncertainty package.
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Medium
7d
340
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Why I Don’t Recommend Bootcamps or Computer Science Degree Programs
- The writer was unable to find a job as a software engineer despite having some available opportunities.
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Medium
7d
49
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Jobs in High Demand in 2025
- AI professionals skilled in building, testing, and maintaining AI models are in high demand.
- Cloud computing is widely sought after, providing various internet-based computer services.
- Translation jobs are still in high demand as AI struggles to understand deep feelings and cultural differences.
- Creating mobile apps remains a rewarding and enjoyable skill in high demand.
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Analyticsindiamag
7d
199
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Perplexity Crosses $100 Million in Annualised Revenue
- Perplexity, the AI search engine startup, has achieved over $100 million in annualized revenue.
- Perplexity reached this milestone 20 months after the launch of Perplexity Pro and has achieved 6.3x year-over-year growth.
- Perplexity offers a free plan, a $20 monthly Pro plan, and an enterprise plan for companies. Developers can also integrate its Sonar AI models with APIs.
- Perplexity is in talks to raise funds between $500 million and $1 billion, valuing the company at $18 billion.
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Medium
7d
365
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How Airbnb Measures Listing Lifetime Value
- Airbnb calculates listing lifetime value to understand valuable accommodation listings for guests and help hosts increase listing value.
- Their framework estimates baseline LTV, incremental LTV, and marketing-induced incremental LTV, segmented to inform supply expansion strategy.
- Challenges in lifetime value estimation arise in multi-sided platforms like Airbnb, where transactions of one listing can impact another.
- Incremental LTV is estimated by subtracting cannibalized value from baseline LTV, addressing the challenge of accurately measuring value added by each listing.
- Marketing-induced incremental LTV measures the additional value created by internal initiatives like marketing campaigns for listing improvement tips.
- The estimation framework focuses on accurate baseline LTV, leveraging machine learning and listing features to predict future bookings.
- During the pandemic, Airbnb faced challenges due to changes in travel dynamics, with strategies implemented to improve model accuracy.
- To handle uncertainty, daily adjustments are made to expected values based on accrued values and updated listing features.
- Estimating lifetime value helps Airbnb provide a better user experience and informs decision-making for listings and marketing campaigns.
- This measurement framework may also extend to other applications, such as Airbnb Experiences listings, to determine the value of experiences based on travel trends.
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VentureBeat
7d
74
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Groq and PlayAI just made voice AI sound way more human — here’s how
- Groq and PlayAI have partnered to bring Dialog, an advanced text-to-speech model, to market using Groq's high-speed inference platform.
- The partnership offers one of the most natural-sounding and responsive text-to-speech systems available, addressing shortcomings in existing voice AI technologies.
- Dialog is available in English and Arabic, making it the first voice AI designed for the Middle East region.
- Groq's specialized processing infrastructure allows Dialog to generate text up to 10 times faster than real-time, providing a significant advantage in latency for conversational AI applications.
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VentureBeat
7d
319
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Observe launches VoiceAI agents to automate customer call centers with realistic, humanlike voices that don’t interrupt
- Observe.AI has launched VoiceAI agents to automate routine customer interactions in contact centers, improving customer experience and reducing operational costs.
- VoiceAI agents are part of Observe.AI's AI-driven conversational intelligence platform, supporting enterprises across the entire customer journey.
- The suite of solutions includes VoiceAI agents, real-time agent assist tools, AutoQA, agent coaching, and business insights.
- VoiceAI agents handle various customer service inquiries using a mix of in-house AI models and partnerships with major AI providers.
- The goal of VoiceAI agents is to free up human agents for higher-value interactions by handling basic customer tasks efficiently.
- Observe.AI's platform offers specialization and ease-of-use, providing a fully integrated solution for customer service workflows.
- VoiceAI agents are designed for contact centers and integrate seamlessly with existing enterprise systems for quick implementation.
- Observe.AI ensures enterprise-grade security with certifications like GDPR, HIPAA, HITRUST, SOC2, and ISO27001, without relying on voice biometrics.
- Pricing is based on completed tasks, offering cost savings between 70-80% compared to using human agents for customer service.
- VoiceAI agents have shown significant improvements for companies, with high containment rates and continuous performance refinement.
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Analyticsindiamag
7d
16
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Can AI Accurately Bridge the Language Divide in India’s Judiciary?
- AI is being used in India's judiciary to enhance accessibility and streamline legal processes.
- AI-powered translation tools are being used to translate judgments into 18 Indian vernacular languages, facilitating language accessibility.
- However, concerns remain regarding the accuracy of these translations, as legal language is intricate and minor errors could impact understanding of cases.
- AI-powered defect detection tools are also being developed to address procedural delays and reduce paperwork errors in the court system.
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1 Like
Medium
7d
70
How to Choose the Best Data Science Training in United States?
- Define Your Career Goals. Understand your career objectives and choose a training program accordingly.
- Check Course Curriculum and Syllabus. Ensure the program covers essential topics and aligns with industry standards.
- Choose Between Online and In-Person Training. Decide based on your schedule and learning preference.
- Accreditation and Certification. Look for accredited programs that offer recognized certifications.
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4 Likes
Medium
7d
54
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Building Trust in ML/AI by Communicating Uncertainty
- Communicating the limitations of ML/AI systems is crucial for building trust and support from non-specialists.
- Clearly defined use cases and communication of uncertainty levels in ML/AI applications are key for better handling of results and avoiding backlash.
- Tools like simple scales, confidence intervals, and explaining drivers of uncertainty help in effectively communicating uncertainty to users.
- Understanding uncertainty drivers like epistemic and aleatoric uncertainties is important for conveying uncertainty levels in models.
- Various techniques like model performance statistics, Bayesian Neural Networks, and Conformal Prediction can be used to estimate uncertainty in ML models.
- Open source libraries such as TensorFlow Probability and Pyro offer tools for applying uncertainty estimation techniques in ML/AI.
- Alternative methods like Monte Carlo Dropout and Deep Ensemble can be used for approximating uncertainty in deep learning models.
- Generative AI presents new challenges for uncertainty communication due to its complexity and proprietary nature, requiring techniques like expressing certainty levels and leveraging multiple models.
- Techniques such as Perplexity, multi-token entropy, and adapting classic neural network uncertainty methods can help assess uncertainty in generative AI models.
- Using open source models to estimate uncertainty of proprietary models can bridge the gap and enable the application of advanced uncertainty estimation techniques.
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Analyticsindiamag
7d
386
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NVIDIA Releases AI Assistant for RTX Gaming PCs, Laptop Support to Follow
- NVIDIA has released an experimental version of the Project G-Assist System Assistant for GeForce RTX desktop users to optimize games and tweak system settings.
- The AI assistant, called G-Assist, runs locally on GeForce RTX AI PCs and allows users to perform various tasks through voice or text commands.
- It can provide real-time recommendations and diagnostics to help troubleshoot system bottlenecks, improve power efficiency, and overclock a GPU.
- NVIDIA plans to add support for laptops in a future update of G-Assist.
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