113.4K
EDEven people who have worked in the field for years don’t know PyTorch and TensorFlow do basically the same thing.
@edhonour
#Tensorflow Transform Module Updates
Dünyanın dört bir yanından insanlardan Tensorflow Transform Module Updates hakkında Reels videosu izle.
Giriş yapmadan anonim olarak izle.
Trend Reels
(12)
231.6K
CA🔥 PyTorch vs TensorFlow: Which Framework Rules the AI World?
🚀 Origins: PyTorch, born from Meta AI's FAIR in 2016, vs. TensorFlow, Google's prodigy launched in 2015.
🧠 Use Cases: PyTorch for rapid prototyping; TensorFlow excels in production-grade deployments!
🛠️ Tooling: PyTorch's simple debugging vs. TensorFlow's robust deployment tools like TensorBoard!
👉 Ready to pick your side? Watch the video to uncover the ultimate framework showdown!
#AI #MachineLearning #DeepLearning #PyTorch #TensorFlow
@cartoons.teaching.tech
2.2K
HAby combining the camera module and TensorFlow with Raspberry Pi, you can relatively easily create a "human tracking robot". by using Tensorflow, which has a wealth of object detection models, it's also possible to track a person's movements in real time. it pairs perfectly with the compact and power-efficient Raspberry Pi
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→ 📹 credit : murasametech ( 🐦 twitter )
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#socialmedia
#electronica
#coding
#project
#raspberrypi
#maker
#makers
#makersgonnamake
#programming
#education
#pcb
#tech
#robotic
#repost
@harris.py
663.6K
HEThat’s the core functionality up and running. 👌
Still plenty of bugs to iron out, plus a full wiring and hardware cleanup to do.
I also need to fine-tune the servo angles in software—some are only a few degrees off but can't be physically adjusted with enough resolution on the spline.
It’s satisfying seeing this finally move after sitting unfinished for years. The red wires are even sun-faded now. 😅 I first built the hardware when I didn’t have the Arduino skills to get it working with my RC setup—but after rebuilding most of the code from scratch, it’s finally coming together.
#hexapod #robotics #arduino #arduinoproject #robotbuild #mechatronics #diyengineering #roboticdesign #fusion360
@hendotech
171.5K
LEImpossible to build just 12 months ago, @farsoontechnologies manufactured our hypersonic precooler last October. Standing more than 1.5m high (5ft), it is one of the most complex, probably THE most complex metal-printed part ever created. Noyron allows us to engineer these objects, but it takes intense collaboration to push the limits of the production process, and encode the real life constraints into to our Computational Engineering Model. Shown last at Formnext in Germany, you will now be able to see at TCT Asia in Shanghai (March 17-19).
@leap.71
22.0K
COPyTorch vs TensorFlow: What’s the difference and which one should you learn?
If you’re diving into machine learning or building your first neural network, you’ve probably seen these names come up everywhere! The TL;DR is:
💡 PyTorch = intuitive, dynamic, and easier to learn
🚀 TensorFlow = scalable, versatile, and great for deployment
But truthfully, you can’t go wrong with either! And we have beginner-friendly courses to help you get started with both.
#PyTorch #TensorFlow #DeepLearningFrameworks #MachineLearning #AIFrameworks #NeuralNetworks #LearnMachineLearning #DataScience #AIforBeginners #CodingForAI #MLFrameworks
@codecademy
831.1K
NIComment "GOOGLE" to get this New Free AI Tool from Google for understanding Github Codebases.
Google just launched CodeWiki. It's a free AI tool. Paste a GitHub repo link. Boom. It turns the whole project into an interactive dashboard.
No more digging through files. Think of it like a map for a messy city. Diagrams show how code parts connect. Like road signs pointing everywhere. Explanations break down the tough spots. Simple words. Clear steps.
Videos pop up too. They explain code tricks. Perfect for quick lessons.
The good news? A built-in chatbot sits right there. Ask it anything. "What's this function do?" It knows the full codebase. Answers fast.
I recently tried it on a big open-source repo. Pasted the link. Asked about a weird module. Got a spot-on reply in seconds. Saved me an hour.
How easy is setup? Head to Codewiki. Drop the repo URL. Done. Handles up to 1.4 million lines. Updates when code changes. Great for new team members. Or jumping into old projects.
Why does this help? Onboarding speeds up. Questions answered on the spot. Like having a smart buddy next to you.
Here's what you get:
1. Visual diagrams. Architecture. Class links. Workflows.
2. Code breakdowns. No guesswork.
3. Chat for stuck moments.
4. Auto-updates. Always fresh.
Limited to open-source now. But it's free. Public preview rocks. Try a repo like TensorFlow. See the magic yourself.
#codewiki #Googleai #githubrepo
@nick_saraev
169.5K
MAGenerative parts are made by an algorithm that simulates the design many times, adding material where it’s weak and removing it where it’s strong. This creates very light and extremely strong parts. Here’s how to do it:
Start with a seed design containing preserve geometries and obstacle geometries. Preserve geometries are features your final part must keep, like screw holes or mounting points. In my drone frame example, every screw location was modeled as a preserve geometry.
Obstacle geometries define where the final part must not intersect. For the frame, I added obstacles for motors, propellers, the screws themselves, and long cylindrical spaces under each screw hole to ensure room for inserting the screws.
Some programs require a starting shape, but Fusion doesn’t. If needed, make a large block around everything and subtract all preserve and obstacle geometries so the starting shape only fills the allowed region while touching all preserves.
Next, add loads and constraints. At least one preserve geometry must be constrained. Constrain whichever feature will be rigid in real life. If a part is pulled between two points, constrain one and load the other. If the part moves freely, like a drone frame, constrain a preserve geometry near the center of mass.
Then apply forces. All preserve geometries need some load or the simulation may fail. A small extra load on each one ensures they stay connected.
Choose the material closest to what you’ll actually use.
Set your objective. Minimize mass creates the lightest part that barely handles the loads. Maximize stiffness creates the stiffest design for a chosen mass. For my frame, I used maximize stiffness with a 55 g target.
Press solve, and you get an extremely strong, lightweight part that also looks super cool.
#cad #fusion360 #engineering
@manafishrov
37.8K
DETransistors are the backbone of modern electronics, enabling everything from AI to electric vehicles. But not all transistors are the same, each type serves a unique purpose in advancing technology.
From boosting signals in microprocessors to controlling high-power circuits in EVs and industrial automation, transistors drive the future of technology.
🔹 IGBTs power electric vehicles and industrial motors
🔹 BJTs amplify signals in audio systems
🔹 MOSFETs enable high-speed switching in digital electroics
🔹 Phototransistors bring precision to optical sensing
🔹 Darlington transistors provide high current gain in switching applications
🔹 SITs operate in high-frequency communication systems
As electronics evolve, transistor innovation is shaping next-gen IoT, 5G, and AI-driven automation.
#semiconductor #electronicsengineering #transistor #microelectrónica #powerelectronics #embeddedsystems #iotdevices #engineeringdesign
@devomech
48.0K
EN4 Actuator Control simultaneously with CAN.
Low-level-control : Impedance Control
——-——-Specifications are below —————
Motor : gartt ML-5210 bldc motor, sunnysky x4108s-17 bldc motor.
Motor driver : drv8302.
Micro Controller : esp-wroom-32.
Encoder : as5600 magnetic encoder.
CAN tranceiver : TJA1051.
Used libraries : simplefoc, TWAI.
Used language : C/C++.
Used 3D CAD : onshape.
#bldc #motor #esp32 #arduino #cpp #coding #3d #print #foc #control #algoritm #pid #control #actuator #impedance #cad #modeling #bipedal #robot #quadruped #onshape #humanoid
@engineering.seojin_n.n
342.6K
STSimple transfer plate that moves in… two directions. This kind of mechanism can enable flexible 2D movement for boxes or parts without complex robotics.
Simple mechanical design. Can move items both X and Y. Easier than full mobile robots in many cases, and useful for storage and sorting systems Sometimes smart mechanics beats complex control.
Credit: Festo
👉Follow @star.ai.media for more amazing tech, and AI insights.
👉Comment "AI" and you will get FREE 9 AI Business Models to Get Rich in 2026
@star.ai.media
87.4K
REYouTube:-Rebuild Tech
#Transformer #ToroidalTransformer #DistributionTransformer #ElectricalEngineering #ElectronicsShorts HindiTech PowerDistribution RebuildTech VillageElectricity
@rebuildtech1
✨ #Tensorflow Transform Module Updates Keşif Rehberi
Instagram'da #Tensorflow Transform Module Updates etiketi altında thousands of paylaşım bulunuyor ve platformun en canlı görsel ekosistemlerinden birini oluşturuyor. Bu devasa koleksiyon, şu an gerçekleşen trend anları, yaratıcı ifadeleri ve küresel sohbetleri temsil ediyor.
#Tensorflow Transform Module Updates etiketi, Instagram dünyasında şu an en çok ilgi gören akımlardan biri. Toplamda thousands of üzerinde paylaşımın bulunduğu bu kategoride, özellikle @nick_saraev, @hendotech and @star.ai.media gibi üreticilerin videoları ön plana çıkıyor. Pictame ile bu popüler içerikleri anonim olarak izleyebilirsiniz.
#Tensorflow Transform Module Updates dünyasında neler viral? En çok izlenen Reels videoları ve viral içerikler yukarıda yer alıyor. Yaratıcı hikaye anlatımını, popüler anları ve dünya çapında milyonlarca görüntüleme alan içerikleri keşfetmek için galeriyi inceleyin.
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📹 Video Trendleri: En yeni Reels içeriklerini ve viral videoları keşfedin
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🌟 Öne Çıkanlar: @nick_saraev, @hendotech, @star.ai.media ve diğerleri topluluğa yön veriyor
#Tensorflow Transform Module Updates Hakkında SSS
Pictame ile Instagram'a giriş yapmadan tüm #Tensorflow Transform Module Updates reels ve videolarını izleyebilirsiniz. Hesap gerekmez ve aktiviteniz gizli kalır.
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💡 En iyi performans gösteren içerikler ortalama 517.2K görüntüleme alıyor (ortalamadan 2.3x fazla). Orta seviye rekabet - düzenli paylaşım momentum oluşturur.
Kitlenizin en aktif olduğu saatlerde haftada 3-5 kez düzenli paylaşım yapın
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📹 #Tensorflow Transform Module Updates için yüksek kaliteli dikey videolar (9:16) en iyi performansı gösteriyor - iyi aydınlatma ve net ses kullanın
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Tensorflow Transform Module Updates Keşfet#modulation#modules#module#tensorflow#modulive#modulate#tensorflow updates