Nazanin 🐹

@nazaninn

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Day 30 of #100daysofcodingchallenge Topic 🎯 React Js today i have learned about • passing data via props and Css module • passing components as children that's all i have done today. #100daysofcodechallenge

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Day 33 #100daysofMachineLearning Dived deeper into transfer learning, although just on a conceptual level. Also learnt about multi-task learning which is a pretty cool technique used in autonomous driving (self-driving cars) to learn multiple tasks with a single neural network.

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Really impressed with the depth of knowledge shared in this Advanced DevOps article. The emphasis on security and automation aligns perfectly with the industry’s move towards Infrastructure as Code (IaC). Thanks for sharing! 824 $DEGEN

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Day 32 #100daysofMachineLearning I finally decided to start working on kaggle projects. I should have started this a while back, but anyways we're here now. I really hope to stay consistent with it. It's a great way to practice what I've learnt and build projects alongside.

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This post is a treasure trove for any data enthusiast! The detailed comparison of performance improvements in TensorFlow and PyTorch gives great insight into their practical applications. Can’t wait to experiment with the new visualization tools mentioned. Great job! 832 $DEGEN

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Day 31 #100daysofMachineLearning Amongst other things, I learnt about error analysis and how it can be used in improving the performance of your model. It's a manual way of checking and analyzing the cause of wrong predictions and using the insights to improve your model.

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Navigating the early stages of learning to code can be daunting, but this post lays out common issues and actionable solutions so well. It’s reassuring to know that these problems are universal and surmountable. This kind of guidance is invaluable for beginners. Great work on compiling it! 842 $DEGEN

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Day 30 #100daysofMachineLearning Already started the third course of the DL specialization which is on "Structuring Machine Learning Projects". This course moves beyond all the technicalities and focuses on the strategy and best approach to apply when working on ML projects.

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Great progress on Day 26 of your #100daysofcodechallenge! 🚀 Diving into React JS is a fantastic choice. Understanding the differences between class and function components is key to mastering React’s versatility. 🛠️ 860 $DEGEN

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Day 29 #100daysofMachineLearning Completed the second course of the Deep Learning Specialization 🚀.

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Embarking on a 30-day journey to master SQL is an ambitious and exciting challenge! Your roadmap is a beacon for many aspiring data enthusiasts. Can’t wait to see the progress and insights you’ll share along the way. Keep the updates coming! 🔥 884 $DEGEN

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Day 28 #100daysofMachineLearning Learnt about the two major school of thoughts on hyperparamter tuning (pandas vs cavier approach). You can either choose babysit one model and monitor its performance or train multiple models in parallel and pick the one that works best.

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Great progress on DAY 24 of the #100daysofcodechallenge! 🚀 Diving into React JS is a big step, and it sounds like you’ve covered some essential ground. Understanding the core concepts of React and how it differs from vanilla JS is crucial for building dynamic web applications. 383 $DEGEN

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This SQL Zero to Hero guide is a game-changer! The step-by-step approach makes understanding complex queries a breeze. Highly recommend for anyone looking to upskill! 555 $DEGEN

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🌀 Cast and get 3 free spins to earn points. Points will be exchanged for tokens at the end of the 1st season. 🫂 Get 3 more spins for each friend you invite. Read the «Rules» section to learn more. ☀️ Enter Onchain Summer with /pill

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Day 27 #100daysofMachineLearning Rewatched the tuning process video to gain a better intuition. Noted that the learning rate is the most important hyperparameter to tune during training. Also learnt about the methods used in selecting the best values for the hyperparameters.

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969 $DEGEN thanks for this information

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⛓ All trenches lead onchain

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Day 26 #100daysofMachineLearning Completed the programming assignment for the optimization algorithms. Over to the last week of the course 🚀.

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