At DataSource AI, we are driven by a singular mission - to democratise the immense power of data science and AI/ML by harnessing our data expert community

London, England
Joined January 2020
We’re thrilled to announce the VN2 Inventory Planning Challenge – the first public inventory planning datathon! πŸ† €18,000 prize pool Leading supply chain professionals πŸ‘€ – and with amazing sponsors @SupChains,@FlieberInc, Daybreak.ai πŸ”—datasource.ai:443/en/home/da…
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Data-driven creativity blends artistic vision with data science insights, revolutionizing video content creation. This approach transforms data into a guide for crafting engaging and relevant content.
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1/ 🧡 Dive into the world of #AI in unstructured data mining! 🌐 In today's digital era, we produce vast amounts of data daily, categorized as structured and unstructured. The latter holds immense untapped potential. Let's explore the challenges and opportunities! πŸš€ #DataScience
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πŸš€ MIT researchers have developed GenSQL, a generative AI tool that enhances database searches! This innovative extension of SQL combines probabilistic programming with traditional searches, allowing for complex queries and predictions. πŸ“ŠπŸ” #AI #Database #TechInnovation #MIT
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🧡 Let's talk about evaluating #MachineLearning models! πŸ“ˆ Ensuring your models perform well on unseen data is crucial for success. Here are some key metrics you need to know. #DataScience #AI #ModelEvaluation
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πŸ“Š Looking to advance your career in Data Science? Here are the top 2 online courses for 2024 that can help you master the skills needed to excel in this rapidly growing field. #DataScience
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Are you thinking about using deep learning for your next project? πŸ€” While powerful, sometimes it might not be the best choice. Here are some situations where you should consider avoiding deep learning. #DataScience #MachineLearnirning
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Poisson Distribution: Useful for modeling the probability of a given number of events happening in a fixed interval. Perfect for count-based data! πŸ”’ #PoissonDistribution
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Box-Cox Transformation: Transform your data to make it more normal. This technique helps in stabilizing variance and making the data more suitable for modeling. πŸ”„ #BoxCox
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Power Law Distribution: This distribution shows a functional relationship where a relative change in one quantity results in a proportional change in another. Think of the 80/20 rule! πŸ“
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