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day 10/100 Today i have done Find the repeating element and missing element i have used mathematical approach and also learned the bit manipulation version of the problem (not so intuitive). I have also done Maximum Product sub array question

Today's Contest, "Somewhat Redeemed" from yesterday's contest (could only solve 1/4 for the first time). Today's Question: 1. Find the Child Who Has the Ball After K Seconds Intuition: Can do Math, or Run Simulation Math Solution: if k is less than n then return k else check the k/n if it's even, then k%n, if k/n odd then n- k/n 2. Find the N-th Value After K Seconds Standard Prefix on k row't row, State is: dp[i][k] dp[i][k] = (dp[i][k] + dp[i-1][k]) Final SubProblem: dp[N-1][k] 3. Maximum Total Reward Using Operations I: 0/1 Knapsack but with a Twist dp[N][sum = 2000*2000] will give TLE/MLE but Sum will never exceed 4000, Take This testCase: [2000, 1, 2, 1999, 3, 2000, 1998] so if we take 1999 and next we take 2000 then 3999 which makes the take condition false as Max value of reward will be 2000 so Max sum will be 4000 so dp[N][4008] which will pass for the 3rd Question.

Excited to share Chapter 2 of my series on problem-solving! Problem Transformation through Function Composition #FunctionComposition #ProblemSolving #FunctionalProgramming

Illustrates the value of understanding the fundamentals 🤔

Analyzing Strategic Plays in CS:GO with Gen.G

Continuing into the math of the transformers, the second video of the three by Luis Serrano gives a good idea into cosine similarity, attention and importance of QKV. Normalization cannot be done with straightforward averaging approach as there may be exact opposite dimension value which will cancel out leading to a wrong normalization. In a simplified statement, the value of 'Attention' basically indicates that we find out to what extent can one of the words be 'adjusted' towards another word which is in the context window for the use of the task. When used ahead in the conversation, the modified coordinates of the words are used and not the initial. This is the factor which differentiates the transformers from other architectures. While Key and Query vector are used to find the similarity, value vector along with attention weightage process is used to predict the next word, translation, summarization and similar tasks. #GenAI #Transformers #Self #Attention #CosineSimilarity #QKV Video - https://lnkd.in/gQDwZgj5

A new lecture in the Course: "Design and Analysis of Algorithms", has been published: https://lnkd.in/dEHmyiUP Lecture 22: Karger's Algorithm - Part 4 This lecture is the finale in the series about Karger's algorithm. Karger's is a Monte Carlo randomized algorithm to find the min cut in a graph that is almost correct in efficient time. In this last lecture we introduce an extension of Karger's algorithm, called Karger-Stein that makes smart moves regarding the repetition of the base algorithm, that is, repeat when necessary, to avoid starting over. We give formal proofs of the efficiency of the algorithm (an exponential speedup over the original Karger's) as well as an analysis of its probability of success. The instruction language is Arabic, however, all material, slides, definitions, concepts, examples, illustrations, etc., are all given in English.

___;In KLISHk dictionary: 1. Every computer character is a real life word && human experience of feeling. 0. Every thought your brain’s 86 billion neurons tell you is the KLISHk word definition(s).___

Restart!! Today was #Day-01 of LEVEL UP Series. Today's Topics: 1. DSA - Graphs - 3 hrs -Topological Sort. - Kahn's algorithm. - Dijkstra's algorithm. 2. Aptitude - 2.5 hrs. 3. OS - 3 hrs Time spent : 8 hrs 30 min.

New Post: Deep dive: Transformers by Gemma, Iterative Reasoning PO, inner work of Transformers Demystifying Transformers with Google’s Gemma, boosting reasoning tasks with Meta’s Iterative Reasoning Preference Optimization, and enhancing und https://buff.ly/3SNUou3