Nikhil Ninan PhD

AI isn’t the end for data practitioners. Very much the opposite. Barry McCardel, the co-founder and CEO of Hex, is bullish on a new golden era of data teams, because, “There's an infinite demand for insight and an infinite demand for data work.” Barry joins Tristan Handy on the Analytics Engineering Podcast to discuss the hype cycle of data science, how AI is different, the experience of building AI products, and how AI will impact data practitioners. https://lnkd.in/d-hfmisr

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We've looked into the distribution of data roles within 40 top data teams across analysts, data scientists, data engineering, analytics engineering and machine learning. → The median proportion of people in insights roles is 46%, slightly higher than the 43% in data engineering roles. → These numbers vary significantly by company. Part of this is semantics. Some companies avoid using analysts and refer to everyone as a data scientist. Others have different boundaries for where data and analytics engineers’ work begins and ends. → Larger companies have a higher share of people in machine learning roles. One explanation for this is that they’re more likely to have found product-market fit with their machine learning implementations. https://lnkd.in/dmYD3ytQ

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Thank you to Open Data Science Conference (ODSC) for inviting me to speak at #ODSCEurope last week. At Applied Data Science Partners, we use cutting edge Generative AI models to deliver for our clients. But we also use a range of other AI and machine learning techniques, so it was a pleasure to speak about ensuring the right solution is used for the right problem, and the value of more classical machine learning techniques in many scenarios. #AI #GenAI #DataScience #MachineLeaning

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🤗 We're still coming down from the high that was Big Data LDN! If you couldn't make it, or were just completely overwhelmed by the overload of talks, we've got you covered! 🧠 We've compiled our top data culture insights, to help you focus on what should be front of mind in your organisation. ⤵ Check out our latest blog and leave us a comment to share which takeaway resonated the most with you! #DataLiteracy #DataCulture #DataBlog #BigDataLDN

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Can AI predict the future? Check out Courtney Bonner's article on behavioural forecasting and use cases: https://lnkd.in/eaG2efJ #CasinoAI #PredictiveAnalytics #ThrowbackThursday

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#Knowledge is at the heart of your business—knowing better means doing better. That's the power of integrating #ReasoningAI (and not just #GenAI) & #KnowledgeGraph into your data and content strategy. And it's not just us saying it; Gartner's experts agree! 😉 #DataStrategy #KnowledgeGraph #KnowledgeOperatingSystem #CognitiveAssetManagement

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Ryan O'Sullivan covers key topics such as model training, validation, calibration and budget optimisation, all using the powerful pymc-marketing python package, in his latest article. Read now! #MachineLearning #DataScience

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Follow along Jarom Hulet's clear and concise explainer to understand why homoscedastic errors are required for valid standard errors in linear regression, how to calculate heteroscedastic robust errors, and why the latter remove the need for the homoscedastic assumption.

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I'm thrilled to share a bonus episode of the Data Today #podcast on #AIAppreciationDay. This one is particularly special to me: Data and Artificial Neural Networks with Damian Borth.    Neural networks are the backbone of many #AI and machine learning systems. But how can they be applied to real-world scenarios?    I had the incredible opportunity to sit down with Damian Borth, Professor of Artificial Intelligence and Machine Learning at the University of St.Gallen and director of its Computer Science Institute. Damian's ground-breaking work on neural networks spans several crucial areas, including climate change, financial fraud detection, and text-to-speech. It's no wonder he’s a recipient of the prestigious Google Research Scholar Award!    In this episode, we dive into:  What #neuralnetworks are and what they do How their application can help tackle global challenges Insights from Damian's vast experience and groundbreaking research   I found our conversation incredibly enlightening and inspiring, and I can't wait for you all to hear it. Tune in to discover how #ArtificialIntelligence and neural networks could help save the world! #TechForGood https://lnkd.in/ePTYn3AC #MachineLearning #DataScience #Innovation #Research #Data #Technology

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Its a jungle out there! 🌿 Take a look at this manuscript mapping similarities/differences in #RWE recommendations across #regulatory and #HTA guidance documents/frameworks. Becaris Publishing Limited #fitforpurpose #RWD #evidence #realworlddata #dataquality #bigdata #regulatoryaffairs #marketaccess #patientjourney #patientoutcomes #clinicaltrials #realworldevidence #drugdevelopment #pharma #FDA #EMA #reimbursement #healthcare #heor #healtheconomics #medicalaffairs #ISPOR #access #ISPE #pharmacoepidemiology

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🦆 What makes a Great Data Leader? 🦆 Data Engineers London recently had the pleasure of hearing from Nik Walker, Head of Data Engineering at Co-op, who delivered an absolutely quack-tastic talk on the power of human-centric leadership for data teams. Nik certainly brought his learned own views, but not just that; he guided us through a thoughtful exploration of how empathy, trust, and open communication are the real engines driving successful teams. And yes, there were a few quacks along the way to keep things lively! 🦆😅 The best part? Nik’s insights aren’t just for those leading teams - there’s something valuable here for anyone working in data. Trust us, it’s worth a watch! Some of the highlights! 🎥 Human-Centric Leadership 🤝  People over technology. Understanding your team’s emotions and needs is key to tackling any challenge. Trust & Vulnerability 🚀  Effective leaders build trust by being open and showing vulnerability—this creates a space where teams feel empowered to innovate and take risks. Psychological Safety 💬  Safe spaces aren’t just buzzwords. They’re essential for fostering honest conversations, admitting mistakes, and driving innovation. Inclusivity 🌍  Valuing every voice on the team leads to richer ideas and solutions—diversity truly drives creativity. Continuous Learning 🧠  Never stop learning! Encouraging ongoing development keeps the team adaptable and engaged in a fast-changing field. And perhaps the most resonant takeaway? Servant Leadership 🏅 Prioritising the team’s needs above your own cultivates a loyal, motivated, and highly effective team. Check it out now! - https://lnkd.in/eN8d4rye Thanks to our sponsors Kyndryl for your support, and Zego for hosting us! And thanks from us to you all in the community! Make sure you join our community page for the next event! Anna Aleshko, Jamie Marney & Harry Duddridge #DataEngineering #Leadership #EmpathyInTech #Data #TeamCulture #ContinuousLearning #Humancentricleadership

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🚀 Game-Changer Alert for Python Developer🚀 If you haven’t checked out uv yet, now’s the time. Built by the team at Astral , uv is a supercharged Python package manager written in Rust. It started as a pip alternative, but it’s grown into something much bigger. Here’s what uv brings to the table: - Python Project Handling Done Right: From generating cross-platform lockfiles to managing dependencies—uv does it all. - Tool Management: Install and run command-line tools in isolated environments. - Python Installation Simplified: Bootstrapping and managing Python versions has never been easier. - Seamless Script Execution: Execute single-file Python scripts with embedded dependency metadata—no extra hassle. uv is revolutionizing the way we handle Python development, making it faster and more streamlined than ever. If you’re serious about your Python projects, uv is definitely worth a look. #Python #Rust #DevTools #PackageManager #uv

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Tomorrow, Thomas Wood will be presenting the Harmony project at PyData London (organisers: Ian Ozsvald, Prashant Tiwari). 🤷 What does Harmony do? 👉 Psychologists and social scientists often have to match items in different questionnaires, such as "I often feel anxious" and "Feeling nervous, anxious or afraid". 👉 This is called harmonisation. 👉 Harmonisation is a time consuming and subjective process. 👉 Going through long PDFs of questionnaires and putting the questions into Excel is no fun. ✅ Enter Harmony, a tool that uses natural language processing and generative AI models to help researchers harmonise questionnaire items, even in different languages. 🌐 https://lnkd.in/drXNbRK #machinelearning #dataanalytics #analytics #artificialintelligence #ml #fastdatascience #naturallanguageprocessing #nlp #predictiveanalytics #bigdata #datascience #ai #neuralnetworks

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“Data is important for everyone, and it should be approachable for everyone, meaning that you don't need to be a data scientist or some sort of data expert to be able to use data.” - William Bett Listen to Ryan and William discuss the importance of data in an approachable way on the Making Better Decisions podcast. https://bit.ly/3BbIUuu #CanopyAnalytic #MakingBetterDecisions #Data #Podcast #DataAnalytics

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TLF Gems: Why Data Cleaning Matters. This one won't be for everyone, but for some of you it may be a gamechanger. A great mini tutorial from Dr Albert Rapp on tidying up data in R (and if this doesn't float your boat, make sure you check out Albert's other tutorials). "Even if you can get the data into R with {rvest}, it will come in a really messy format. And if you don’t have the right tools to clean that up, you’ll be stuck with cleaning the data before you can even begin to build the table." https://lnkd.in/eSK6ejWb

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300+ other organisations have transformed thier approach to data and analytics with the help of In-Form by Homeless Link. If you’re looking to do the same, check out our new blog post to see how easy it is https://lnkd.in/daFwMXme Highly recommend it if you’re aiming to maximise your data’s potential and get the most from your investment! #DataStrategy #DigitalTransformation #CustomerSuccess

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Check out James Bowkett, our Technical Delivery Director, as he discusses "Mastering Data Centric Engineering: 12 Principles for Success" in his talk from Data Science Festival 2024. Data is everywhere, and so too are data-centric applications. As the world becomes increasingly data-centric, and the volumes of that data increase over time, data engineering will become more and more important. If we're going to be dealing with petabytes of data it will be better to get the fundamentals in place before you start, rather than trying to retrofit best practices onto mountains of data. This only makes a difficult job harder. The 12-factor app helped to define how we think about and design cloud native applications. In this presentation, James discuss 12 principles of designing data-centric applications that have helped him over the years across 4 categories: Architecture & Design, Quality & Validation (Observability), Audit & Explainability and Consumption. Watch the recording here: https://lnkd.in/ea5nYzYh #DSFoktoberfest #DataEngineering #DataPlatforms #datasciencefestival

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