• Soft skill – +1 mindset

    Soft skill – +1 mindset

    Recently I reflected on my professional career on things that I have done differently earlier on in my career versus now. One thing that stood out is, that I practice the +1 mindset now. The +1 mindset considers not just my views, but also the others that I interact with. Early on in my career,……

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  • Things they didn’t teach you in software engineering

    Whenever you feel disillusioned about the mismatch in promises between what you were taught in university/bootcamp versus what you actually worked on in a job. I recommend reading this article, https://vadimkravcenko.com/shorts/things-they-didnt-teach-you/. It is written for software engineering, but many points mentioned apply to data science/analytics as well.

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  • Data science solutions – Build vs buy

    Data science solutions – Build vs buy

    Many data scientists are working in companies with less advanced technology infrastructure. But these companies still wish to solve their business problems with the help of data science / analytics. At this point usually a question arises, “Should we build or buy a solution to solve this problem with data science?”. As nicely pointed out……

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  • Being a data scientist in consulting

    A very accurate and vivid description of being a data scientist in a consulting context. I can definitely say that I have experienced this myself, and it does take a while to get used to presenting comfortably (therefore confidently). But like it or not, the holy grail in data science has always been about connecting……

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  • Delegating to chatGPT & Stable Difussion

    Delegating to chatGPT & Stable Difussion

    This week, I am jumping on the bandwagon by delegating the task of creating my LinkedIn post to chatGPT (for text) and Stable Diffusion (for image) with the following prompts. ⌨ chatGPT : Can you write an opinion article, discussing your opinion on this topic, “In the future, do you see a shift in companies……

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  • State of DS Survey by Anaconda – Skill Gaps

    State of DS Survey by Anaconda – Skill Gaps

    According to the State of Data Science survey done by Anaconda, the top 5 most important skill gaps in data science are: ⭐️ Engineering skills ⭐️ Probability and statistics ⭐️ Business knowledge ⭐️ Big data management ⭐️ Communication skills These skill gaps cut across multiple knowledge domains, from technical skills to soft skills, reflecting the……

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  • Illustrated stable diffusion from Jay Alammar

    Illustrated stable diffusion from Jay Alammar

    If you are interested in knowing how Stable Diffusion generates amazing AI arts, but are put off by the steep technical details, This illustrated guide from Jay Alammar should help you, https://jalammar.github.io/illustrated-stable-diffusion/. The guide helpfully breaks down the model into components and substitutes complex equations with simple flowcharts. P/S: I also highly recommend his illustrated……

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  • Short review of Designing Machine Learning System

    Short review of Designing Machine Learning System

    I have finally finished “Designing Machine Learning Systems” after a few weekends of focus reading. It is one of the rare technical books that I finished in its entirety, and I thoroughly enjoyed it. Just to offer a quick book review below. The book is amazing in the following aspects: ✅Provides a high-level overview of……

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  • Automatic speech recognition – Whisper OpenAI

    Automatic speech recognition – Whisper OpenAI

    Whisper is a recently released transformer-based automatic speech recognition (ASR) model from OpenAI. It can be used for: 🗣Language identification 🗣Voice activity detection 🗣Multi-lingual speech recognition 🗣Multi-lingual speech translation When evaluated on the ESB datasets (including LibriSpeech, Common Voice), Whisper outperformed Conformer RNN-T from NVidia and Wav2Vec2 from Meta. Link to blog: https://openai.com/blog/whisper/Link to repo:……

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  • Data versioning

    Data versioning

    “Data versioning is like flossing. Everyone agrees it’s a good thing to do, but few do it.” ~ Chip Huyen, Designing Machine Learning Systems Unlike code versioning, it is a lot more difficult to implement data versioning in data science / machine learning projects. It is because of the following reasons: ➡️ Data is often……

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