1/8/2024 0 Comments Tiny decisions github![]() ![]() In a decade, I was topped by someone I hadn’t noticed. From flying high for a decade, I had been beaten hands down. As I checked the rank list, it was the truth. I got around 150”ġ50? Rank or marks? From DPS Kanpur, where I was top? This was suddenly the biggest plot twist I had experienced in my life. I was just going to say I plan to join IIT Bombay or IIT Delhi. What was it?”īefore the person finished typing the whole message, I continued with my confidence that my rank was 638 I replied confidently that I had done well and I was joining IIT Bombay. I hardly focused on who the others where. Do you remember me? What are you doing now?”Īs you remember, I was one of the best kids. “Were you at DPS Kanpur in 1st standard?” I picked science, took the JEE, and made it to IIT BombayĪ few days after my result, and congratulations on my post, my Facebook message lit up. I was doing so well that it was clear nothing could stop me ![]() I ended up at the top of my school in Pune in my 10th board exams. My streak of doing well in school continued long afterwards After all, everyone believed I was destined for bigger things. I wouldn’t notice most students except my close friends or the other toppers. My eyes always were on the bigger prize ahead. I would come top of my class in school almost certainly from 1st to 3rd gradeĭPS Kanpur was one of the best schools in the city. Once you build something valuable and look back, this will be the best experience of your career. It’s not a hard rule to fit everything into scrums. Be patient when the team responds to your questions with “I don’t know”. Uncertainty is not a “loving” concept in program management. It is becoming even more crucial for the planners to work closely with the engineering team using/building this technology while formulating the strategy and defining timelines. A lot of time, decisions need to wait for the results from the experimentation. It has made the planning tougher to deliver value in a definite time. It’s hard to understand the model behavior. With some explainability measures, teams could understand the reasons behind results (to a certain extent). When teams were building their models, they knew about training used for model training. Uncertainty about the value generation, cost/efforts, timelines, and potential risks, makes it uncomfortable to many teams while using/interacting with this technology.ĪI/ML was always a probabilistic technology but was not this uncertain. This element of uncertainty multiplied 10X because of GenAI. What makes it hard for Leadership and program managers working on GenAI Strategy development/project management is uncertainty. With its clean and concise code, Tiny-NN offers a great learning platform for those who want to deepen their understanding of the inner workings of neural networks. GitHub - PraneethVasarla/tiny-nn: Tiny-NN is a lightweight neural network library built entirely in NumPy, designed to help developers understand the nitty-gritty details of neural networks. If you're interested in learning more about TinyNN or collaborating on a project, feel free to reach out!Ĭheck out the project on GitHub: #machinelearning #deeplearning #neuralnetworks #opensource #python I'm excited to see what kind of innovative models we can build together. It's still a work in progress and I'm looking forward to sharing my progress and insights with the community. Plus, the open-source nature of the project means that I can contribute to the wider community of data scientists and AI researchers. With TinyNN, I can dive deep into the inner workings of neural networks, experiment with different architectures, and gain a deeper understanding of how machine learning models function. I'm excited to share that I've just started working on TinyNN, a lightweight neural network library built in Python using NumPy! My goal is to explore the nitty-gritty details of neural network libraries and build my own models from scratch. ![]()
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