Dive into the performance benefits of NumPy with Intel’s own Bob Chesebrough. You can speed up Pandas natively by leveraging NumPy powered by oneAPI, to solve Pandas apply performance issues. Find out how right here. https://intel.ly/3I7rU8X #Developer #oneAPI #Training
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Day 91/100 of #100DaysofCode! 🎉 Mastered Routes & Templates in Flask with CS50 Harvard! 📚💻 Key takeaways: ✨ Routing best practices ✨ Template rendering ✨ Flask framework fundamentals Thanks to CS50 Harvard & #100DaysofCode community! 🙏 Next stop: 100 days! 🔥 #CS50Harvard #Flask #WebDevelopment #CodingCommunity #LearningJourney #GrowthMindset"
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Take a peek at my GitHub project where I've built a simple full-fledged machine learning pipeline, starting from the very basics like data ingestion and transformation, all the way to building and evaluating models. I even used cool tools like MLflow to keep track of my experiments and Docker to make sure everything runs smoothly when it's deployed. Plus, I deployed it locally using Streamlit, so you can see it all in action! It's like taking a behind-the-scenes tour of how machine learning magic happens, from messy data to polished predictions. Check it out and let me know what you think! https://lnkd.in/dNi6KVQE
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Have you ever thought of JSON as a treasure map? 🗺️ Well, if you're struggling to understand what JSON is, this explanation might help 💡 #learncoding #codingtips #learningtech
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🎉numpy 2.0.0 🎉just released this week. So whats so special about that? Well, apart from a bunch of new features and removal of some deprecated API's, this release is the first major release after numpy 1.0 which was released in ... 2006! That's right, numpy has been stable with no breaking changes for __18 YEARS__ until finally now a new major version. In this era of move fast and break things, numpy has been an ocean of stabilily, which has enabled large frameworks like pandas to build on top of it with full confidence.
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🚀 Exciting News! I just published my first article on Medium! 🎉 As a data engineer and a big fan of Apache Airflow, I’m passionate about improving the quality and consistency of Airflow DAGs. In this article, I dive into how you can use Python’s Abstract Syntax Tree (AST) to lint your DAGs and standardize workflows across your team. Plus, I introduce DAGLint, a tool we built internally at Next Insurance to enforce best practices and ensure smooth operations. Check it out and let me know your thoughts!👇 #DataEngineering #Airflow #Python
Mastering Airflow DAG Standardization with Python’s AST: A Deep Dive into Linting at Scale
link.medium.com
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🌟 Just completed Day 37 of the #100DaysOfDSAChallenge, revisiting core Data Structures and Algorithms concepts and mastering the Sudoku Solver problem on LeetCode. Excited for the journey of continuous learning and improvement! Stay tuned for more updates! 💪 🕒 Time complexity: O(9(N∗N)) 🔍 Space complexity: O(N^2) #DataStructures #Algorithms #LeetCode #ContinuousLearning #ProgrammingJourney
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🚀 Day 35 of my 100 Days of Code Challenge on LeetCode! 💻 Today's problem was "Word Search II," a challenging algorithm-based problem where I implemented a Trie to efficiently search for all words on a given board of characters. 📝 Challenge: 212. Word Search II It was quite an exercise in combining depth-first search (DFS) with Trie data structure to find words constructed from sequentially adjacent cells. A great way to deepen my understanding of advanced search algorithms! Way towards next challenge🚀 #CodingJourney #100DaysOfCode #LeetCode #ProblemSolving #Trie #DFS #Algorithms
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📊 Day 11 🔤 Today, I explored the power of Python’s built-in `title()` function. This handy tool effortlessly transforms strings by capitalizing the first letter of each word, making text formatting a breeze. Whether cleaning up user input or enhancing the readability of data, `title()` adds a touch of elegance to our strings. 🌟🖋️ Let’s celebrate the simplicity and utility of built-in functions! What’s your go-to string manipulation function? Share below. 🤓 #CodingMagic #PythonBuiltIns #Day11Challenge
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How to Create Well-Styled Streamlit Dataframes, Part 1: Using the Pandas Styler
How to Create Well-Styled Streamlit Dataframes, Part 1: Using the Pandas Styler
towardsdatascience.com
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🌟 Just completed Day 36 of the #100DaysOfDSAChallenge, revisiting core Data Structures and Algorithms concepts and mastering the Valid Sudoku problem on LeetCode. Excited for the journey of continuous learning and improvement! Stay tuned for more updates! 💪 🕒 Time complexity: O(1) 🔍 Space complexity: O(1) #DataStructures #Algorithms #LeetCode #ContinuousLearning #ProgrammingJourney
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