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Author: Josh Starmer, Ph.D. Book Amazon link: https://www.amazon.com/dp/B0BLM4TLPY Youtube link: https://www.youtube.com/@statquest Chapter 1 : Fundamental Concepts of ML What is Machine Learning (ML)? According to the author, ML is a collection of tools and techniques that transforms data into decisions. Basically, ML is about 2 things: Classifying things (Classification) and...
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My notes from an excellent YouTube video covering key business concepts taught at Stanford Business School, condensed into 28 minutes of actionable insights. Read more
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Master 10 essential German time and frequency combinations that native speakers use daily. Learn formal vs. informal usage, plus bonus comparative patterns. Read more
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Learn how to practice German by yourself using sentence transformation techniques. Master word order, tenses, and modal verbs through progressive complexity building. Read more
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When it comes to language learning, focusing on phrases and sentences rather than isolated words can make a significant difference. While memorizing vocabulary lists might seem like a straightforward approach, it often leaves learners struggling to use those words in real-life situations. Words alone rarely convey complete meaning; context is...
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Learn German adverbs: types, formation, placement, and usage. Essential words for describing how, when, where, and why actions happen. Read more
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Learn German personal pronouns in all cases: Nominativ, Akkusativ, and Dativ. Essential pronouns for replacing nouns and building fluent sentences. Read more
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Learn the German Dative case: indirect objects, articles, prepositions, Wechselpräpositionen, and Dativ verbs. Essential for German grammar mastery. Read more
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Learn German separable and inseparable verbs: prefixes, word order, and usage patterns. Essential for understanding German sentence structure. Read more
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Learn German modal verbs: können, müssen, wollen, sollen, dürfen, mögen, and möchten. Essential verbs for expressing ability, necessity, and desire. Read more
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Learn the German Accusative case: direct objects, articles, pronouns, and when to use Akkusativ. Essential grammar for German sentence structure. Read more
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Learn time expressions in German: telling time, days of the week, months, seasons, and useful time phrases for daily conversation. Read more
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Learn how to ask questions in German: yes/no questions, W-questions, and question formation rules. Essential for German conversation. Read more
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Learn German verb conjugations and how verbs change according to the subject. Essential foundation for German sentence structure. Read more
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Learn how to use possessive articles (my, your, his, her, etc.) in the nominative case in German. Essential grammar for expressing ownership and relationships. Read more
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Nominative pronouns are personal pronouns that replace the subject in a sentence. They show who or what is doing something, e.g., I am tired. Deutsch: Pronomen im Nominativ sind Personalpronomen, die das Subjekt im Satz ersetzen. Sie zeigen, wer oder was etwas tut, z. B. Ich bin müde. Singular Plural...
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This blog post provides beginner-friendly (A1 level) German vocabulary and example sentences grouped by common topics such as travel, family, health, media, and everyday life. Each section includes color-coded tables for key nouns and practical sentences with English translations, helping learners build essential language skills for real-life situations. Read more
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Master the formation of German past participles (Partizip Perfekt) for regular and irregular verbs with clear rules and examples. Read more
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References: Triton In a typical machine learning(ML) work flow, we program the feature production, training, and inference. We do that mostly using frameworks to write high-level program and not have to manage the low level details required for ML or deep learning (DL). The pytorch or tensorflow (frameworks) calls the...
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Master 10 essential German time and frequency combinations that native speakers use daily. Learn formal vs. informal usage, plus bonus comparative patterns. Read more
Published:
Learn how to practice German by yourself using sentence transformation techniques. Master word order, tenses, and modal verbs through progressive complexity building. Read more
Published:
Learn German adverbs: types, formation, placement, and usage. Essential words for describing how, when, where, and why actions happen. Read more
Published:
Learn German personal pronouns in all cases: Nominativ, Akkusativ, and Dativ. Essential pronouns for replacing nouns and building fluent sentences. Read more
Published:
Learn the German Dative case: indirect objects, articles, prepositions, Wechselpräpositionen, and Dativ verbs. Essential for German grammar mastery. Read more
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Learn German separable and inseparable verbs: prefixes, word order, and usage patterns. Essential for understanding German sentence structure. Read more
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Learn German modal verbs: können, müssen, wollen, sollen, dürfen, mögen, and möchten. Essential verbs for expressing ability, necessity, and desire. Read more
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Learn the German Accusative case: direct objects, articles, pronouns, and when to use Akkusativ. Essential grammar for German sentence structure. Read more
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Learn time expressions in German: telling time, days of the week, months, seasons, and useful time phrases for daily conversation. Read more
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Learn how to ask questions in German: yes/no questions, W-questions, and question formation rules. Essential for German conversation. Read more
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Learn German verb conjugations and how verbs change according to the subject. Essential foundation for German sentence structure. Read more
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Learn how to use possessive articles (my, your, his, her, etc.) in the nominative case in German. Essential grammar for expressing ownership and relationships. Read more
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Nominative pronouns are personal pronouns that replace the subject in a sentence. They show who or what is doing something, e.g., I am tired. Deutsch: Pronomen im Nominativ sind Personalpronomen, die das Subjekt im Satz ersetzen. Sie zeigen, wer oder was etwas tut, z. B. Ich bin müde. Singular Plural...
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This blog post provides beginner-friendly (A1 level) German vocabulary and example sentences grouped by common topics such as travel, family, health, media, and everyday life. Each section includes color-coded tables for key nouns and practical sentences with English translations, helping learners build essential language skills for real-life situations. Read more
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Master the formation of German past participles (Partizip Perfekt) for regular and irregular verbs with clear rules and examples. Read more
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Book: Amazon link Chapter 4: RAG Feature Pipeline Retrieval-augmented generation (RAG) Feature Pipeline: Qdrant vector DB for online serving and ZenML artifacts for offline training. Naive RAG Chunking Embedding Vector DBs Chapter teaches you what RAG is and how to implement it. The main sections of this chapter are: Understanding...
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Book: Amazon link Notes An LLM engineer should have the knowledge in the following: Data preparation Fine-tune LLM Inference Optimization Product Deployment (MLOps) What the book will teach: Data Engineering Supervised Fine-tuning Model Evaluation Inference Optimization RAG For every project there must be planning. And the three planning steps the...
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Resources: Video: Dynamic Arrays Link: The Simple and Elegant Idea behind Efficient Dynamic Arrays Link: What if you had to invent a dynamic array? Dynamic Array should be able to change the shape of the array dynamically. should be able to add/delete element fast should be able to insert/delete a...
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Prerequisites: Dynamic Arrays Hash Usage Hash Implementation Prefix Sums
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To improve the retrieval of the RAG system, you usually need to fine-tune the pre-trained LLM. However, it can also be done by using Instructor models. https://huggingface.co/hkunlp/instructor-xl
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A comprehensive guide to hyperparameter tuning in data science, covering Optuna and other optimization techniques for improving machine learning model performance. Read more
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Ask yourself if the following three statement are true for you or not? I fantasize more than I act. I consume ten times more than I produce. I constantly delay Day#1. If any two of the three are true for you, then you are indeed Lazy but Ambitious. Now, we...
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People want to be rich. They want to have a comfortable living. A bountiful life. They want cars, houses, land, boats, yachts, and much more. They want to be successful. They want to be praised for their excellent work. They want to be recognized, appreciated for their work. They want...
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We do not learn from experience. We learn from reflecting on those experiences. -John Dewey Learning is defined as the modification in behavior through experience. So if you approach the same problem differently from your previous attempt, then we can say you have learned something. This is why the quote...
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Will mini-essays make me a better research paper author? Will it make me a better thinker? Will it make me a better person? These are all questions that I want to find the answer to. May be we will find out in a few year. A deeper understanding of your...
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If you think positive, positive things happen to you and if you think negative, negative things happen to you. This is the law of attraction. But is it always possible to stay positive? Is it possible to think positively when everything around you is going wrong? When you try your...
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This article introduces the TabR model, a retrieval-augmented model designed for tabular data. It is part of a series on tabular deep learning using the Mambular library. Read more
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Authors: SHRIYANK SOMVANSHI, SUBASISH DAS, SYED AAQIB JAVED,GIAN ANTARIKSA, AHMED HOSSAIN Link: https://arxiv.org/pdf/2410.12034 code: My initial thoughts and what I would like to get out of this? Can DL methods outperform Decision Tree based models on tabular data? What is the common reason between different models which works well for...
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Authors: Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux Link: https://arxiv.org/pdf/2207.08815 code: https://github.com/LeoGrin/tabular-benchmark My initial thoughts and what I would like to get out of this? What makes it difficult for learning tabular-data for deep-learning algorithms or even Neural Networks? What is the correct way for benchmarking? Notes on the paper There...
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This paper presents GPTopic, a novel approach combining embeddings, dimensionality reduction, clustering, and LLMs for dynamic and interactive topic modeling with ChatGPT integration. Read more