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🚀 Future in Tech Starts Now Vedam School of Technology 4-Year CS + AI Program Build your coding base for hackathons & colleg
🚀 Future in Tech Starts Now
Vedam School of Technology 4-Year CS + AI Program Build your coding base for hackathons & college life! Learn from Ex-Google & Ex-Microsoft Engineers
🔗 URL 🔗 URL Designed specifically for 11 & 12 ❤️

"Disclaimer: All content on our channel is for educational purposes only. We do not support any iegal or unethical activities
"Disclaimer: All content on our channel is for educational purposes only. We do not support any iegal or unethical activities. We do not force any user to purchase anything. If you wish to talk to us personally or seek assistance, you can buy our subscription, as it is not possible to assist everyone." "Disclaimer: हमारे चैनल पर सभी कंटेंट केवल educational purposes के लिए है। हम किसी भी ilgal या unethical activities का support नहीं करते। हम किसी भी user को कुछ खरीदने के लिए force नहीं करते। अगर आप हमसे personally बात करना चाहते हैं या assistance लेना चाहते हैं, तो आप हमारी subscription खरीद सकते हैं, क्योंकि सभी users को assist करना possible नहीं है।"

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🚀 Want to speed up training in PyTorch by several times? DataLoader has two bad defaults that slow down the process. By fixi
🚀 Want to speed up training in PyTorch by several times? DataLoader has two bad defaults that slow down the process. By fixing them, I got almost 5x speedup. ❌ Problem - .to(device) transfers data to the GPU. - While the GPU is computing, the CPU does nothing. - While the CPU prepares data, the GPU is idle. ⚡️ Solution You need to make the CPU and GPU work in parallel: - In DataLoader, set pin_memory=True - When transferring data, use .to(device, non_blocking=True) - Add num_workers to DataLoader for background loading. ✅ As a result, the CPU prepares the next batch while the GPU is busy with the current one. This eliminates idle time, and training goes noticeably faster.

🔗 Machine Learning Roadmap Whether you're just starting out or looking to refine your skills, this Machine Learning Roadmap
🔗 Machine Learning Roadmap
Whether you're just starting out or looking to refine your skills, this Machine Learning Roadmap breaks down every step
1️⃣ Build a solid foundation in math and stats 2️⃣ Dive into ML algorithms like Linear Regression, SVM, and Clustering 3️⃣ Choose your ML focus, from supervised learning to recommender systems 4️⃣ Master popular libraries like PyTorch, TensorFlow, and Scikit-learn 5️⃣ Gain real-world experience with projects and side gigs

🔗 3 Types of Machine Learning
🔗 3 Types of Machine Learning

🔗 Cheat sheets for Machine Learning and Data Science interviews A developer posted a useful set of cheat sheets for intervie
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🔗 Cheat sheets for Machine Learning and Data Science interviews
A developer posted a useful set of cheat sheets for interview preparation. They contain all the most important information on key ML and DS topics.
Convenient to review before the interview or to brush up your basics.

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🖐 HTML TIPS AND TRICKS

⌨️ Master the CSS Grid
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⌨️ Master the CSS Grid

🔅 Learn CSS Flexbox in 20 Minutes (Course)
Learn how to create responsive websites with this CSS Flexbox Beginner Course. Display: flex; explained in 20 minutes.
In this CSS Flexbox Crash Course for beginners you are going to learn about responsive web design by getting CSS Flexbox explained. How to use display: flex plays a major rule in making a website responsive, resize elements, wrap elements and align html elements anywhere inside a div. Of course you are also going to learn how to center a div.

💸 5 Free APIs to level up your next programming
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💸 5 Free APIs to level up your next programming

⌨️ How to Use Rem Units in CSS!! Rem units in CSS can be used for setting font sizes, margins, padding, widths, and heights r
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⌨️ How to Use Rem Units in CSS!!
Rem units in CSS can be used for setting font sizes, margins, padding, widths, and heights relative to the root element's font-size.

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