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follow me then comment β€œlink” for early access to vlogit and a guide on using Cursor! today is day 119 of building @theofficialvlogit with @karam_aboulhosn today we talk about our onboarding flow and how i revamped it just recently to mimic successful apps like bereal. so far for our new beta testers it’s been working very well! make sure to follow and comment link to get the app before launch! #cursor #cursorcreator #coding #appdevelopment #startup
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follow me then comment β€œlink” for early access to vlogit and a guide on using Cursor! today is day 119 of building @theofficialvlogit with @karam_aboulhosn today we talk about our onboarding flow and how i revamped it just recently to mimic successful apps like bereal. so far for our new beta testers it’s been working very well! make sure to follow and comment link to get the app before launch! #cursor #cursorcreator #coding #appdevelopment #startup
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coding with Composer 2 on the high speed rail in the motherlandπŸ˜† #cursor #CursorCreator #tech #swe #cs
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Engineering Students! Coding Ka Time Aa Gaya πŸ’» #Coding#CProgramming#BTechStudents
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YouTubeSet time - Bound goal
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Build Your Own ChatGPT Bot in Python (in 60 Seconds) #python #coding #programming In this video you'll build a fully working ChatGPT bot from scratch using Python and the OpenAI API. Starting from a single API call, add user input function and then a full conversation loop with memory, all in under thirty lines of code. You'll learn how to initialize the OpenAI client, send messages to gpt-5.4-mini, and structure a growing message history so your bot actually remembers the conversation. All you
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G-Stack just open-sourced by Y Combinator’s CEO is revolutionizing Claude Code operations with 23 tools that automate your entire dev and release workflow. Get the exact system from top startup accelerator Gary Tan, and turn your Claude Code into a smart, fully managed ops team with one command. #gstack #ycombinator #claudecode #startuptech #automationtools
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Andrej Karpathy's explaination of Bigram Language Model explained Bigram LMs, though simple, it provides powerful insight into the inner mechanics of how tokens are processed in language models. This is a pre-amble for what's next: GPT, which is the 2nd part of the series The Bigram model here incorporates: Tokenization, Vocabulary, Negative Loss Function, Cross Entropy, Logits, SoftMax, Optimizer, and AdamW These are essential ingredients to understand in order to build our knowledge on how LLM
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