Published inTowards AICreating a Reasoning Dataset with No Budget.Reasoning Models #2 — The Dataset CreationApr 7Apr 7
Published inTowards AIFrom Training Language Models to Training DeepSeek-R1Reasoning Models #1 — An overview of trainingFeb 17Feb 17
Published inTowards AI7 Practical PyTorch Tips for Smoother Development and Better PerformanceThings I wish someone listed down.Feb 10Feb 10
Aren’t these “new” AI features impractical? — A data scientist’s rant.When Technology’s Hype Outpaces Its Practicality.Aug 15, 2024A response icon1Aug 15, 2024A response icon1
Published inTowards AIBuilding Blocks of Transformers: AttentionThe Borrower, the Lender, and the Transformer: A Simple Look at AttentionMar 28, 2024A response icon1Mar 28, 2024A response icon1
Published inTowards AISimplifying Decorators in Python | A step-by-step approach.Python is one of the simpler languages that we can learn these days. However, despite being the simplest one, it still has a few areas that…Jan 6, 2024A response icon1Jan 6, 2024A response icon1
Making Sense of PyTorch’s to(device) and map_location.Why are there two different approaches to do the same thing? When is one approach better than the other?Aug 26, 2023Aug 26, 2023
NLP -01: Demystifying Regular Expressions | RegEx guide for beginners.One of the most underrated skills any data professional should have when working with stringsAug 5, 2023Aug 5, 2023
Published inTowards AIMachine Learning Roadmap: Community Recommendations 2023RoadMapsJul 14, 2023A response icon1Jul 14, 2023A response icon1
Published inTowards AIData Lifecycle in Production: Defining and Collecting useful data.How do we determine the criteria for “good” and “useful” data? Where can we collect the data from? How much data should we collect?Jun 24, 2023Jun 24, 2023
