Dimitris Katsios (@dkatsios) 's Twitter Profile
Dimitris Katsios

@dkatsios

ML Engineer at LPIXEL. Board Director at MLT

ID: 200998629

linkhttps://github.com/dkatsios/ calendar_today10-10-2010 20:41:26

1,1K Tweet

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Dimitris Katsios (@dkatsios) 's Twitter Profile Photo

Finally there is the 1st PMDA approval of a Deep Learning based software as medical device for brain MRI in Japan. It’s important to see DL applications reaching the final users & not being limited only to research. Congrats to both PMDA and LPIXEL people! lpixel.net/en/news/press-…

MLT (@__mlt__) 's Twitter Profile Photo

CNN Architectures: Dimitris Katsios shows how to extract the most important information from a paper and implement the architecture with tf.keras. Kicking it off with AlexNet | VGG | GoogLeNet | MobileNet | ResNet GitHub github.com/Machine-Learni… Videos youtube.com/playlist?list=…

CNN Architectures: <a href="/dkatsios/">Dimitris Katsios</a> shows how to extract the most important information from a paper and implement the architecture with tf.keras. Kicking it off with

AlexNet | VGG | GoogLeNet | MobileNet | ResNet

GitHub github.com/Machine-Learni…
Videos youtube.com/playlist?list=…
MLT (@__mlt__) 's Twitter Profile Photo

Learn how to implement a CNN Architecture from a paper: Dimitris Katsios released a new notebook and the video tutorial for "Xception: Deep Learning with Depthwise Separable Convolutions". 📚Notebook: github.com/Machine-Learni… 🧑‍🏫Video tutorial: youtube.com/watch?v=nMBCSr…

Learn how to implement a CNN Architecture from a paper: <a href="/dkatsios/">Dimitris Katsios</a> released a new notebook and the video tutorial for "Xception: Deep Learning with Depthwise Separable Convolutions".

📚Notebook: github.com/Machine-Learni…
🧑‍🏫Video tutorial: youtube.com/watch?v=nMBCSr…
MLT (@__mlt__) 's Twitter Profile Photo

Learn how to implement a CNN Architecture from a paper: Dimitris Katsios released a new notebook and video tutorial "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size". 📚Notebook: github.com/Machine-Learni… 🧑‍🏫Video tutorial: youtube.com/watch?v=W4Ubin…

MLT (@__mlt__) 's Twitter Profile Photo

Learn how to implement a CNN Architecture from a paper: Dimitris Katsios released a new notebook and the video tutorial for DenseNet – "Densely Connected Convolutional Networks". 📚Notebook: github.com/Machine-Learni… 📚Video tutorial: youtube.com/watch?v=3ZPJyk…

Learn how to implement a CNN Architecture from a paper: 
<a href="/dkatsios/">Dimitris Katsios</a> released a new notebook and the video tutorial for DenseNet – "Densely Connected Convolutional Networks".

📚Notebook: github.com/Machine-Learni…
📚Video tutorial: youtube.com/watch?v=3ZPJyk…
MLT (@__mlt__) 's Twitter Profile Photo

Learn how to implement a CNN Architecture from a paper: Dimitris Katsios released a new notebook and the video tutorial for "ShuffleNet: An Extremely Efficient CNN for Mobile Devices". 📚 Notebook: github.com/Machine-Learni… 🧑‍🏫 Video tutorial: youtube.com/watch?v=lWMd_w…

Learn how to implement a CNN Architecture from a paper: 
<a href="/dkatsios/">Dimitris Katsios</a> released a new notebook and the video tutorial for "ShuffleNet: An Extremely Efficient CNN for Mobile Devices".

📚 Notebook: github.com/Machine-Learni…
🧑‍🏫 Video tutorial: youtube.com/watch?v=lWMd_w…
MLT (@__mlt__) 's Twitter Profile Photo

Do you want to learn to read original papers and implement deep learning models from scratch? Dimitris Katsios walks you through CNN Architectures, including notebooks, network visualizations and videos! github.com/Machine-Learni…

François Chollet (@fchollet) 's Twitter Profile Photo

Announcement: my book Deep Learning with Python (2nd edition) has been released. 500 pages of code examples, theory, context, practical tips... If you want to really understand how deep learning works, why it matters, and how to use it, this is your book! manning.com/books/deep-lea…

Suzana Ilić (@suzatweet) 's Twitter Profile Photo

Super excited to kick off weekly study sessions at MLT where we'll go through François Chollet's "Deep Learning with Python" and notebooks, led by the amazing Dimitris Katsios! 🙌 Best time to get into Deep Learning! Join us for the first session here meetup.com/Machine-Learni…

MLT (@__mlt__) 's Twitter Profile Photo

Join us tomorrow for "Deep Learning with Python: Mathematical building blocks of neural networks (Chapter 2)" with Dimitris Katsios #machinelearning #deeplearning #math 🤖 meetup.com/Machine-Learni…

MLT (@__mlt__) 's Twitter Profile Photo

Join us today for Deep Learning with Python Chapter 3: Introduction to Keras and TensorFlow 🙌 with Dimitris Katsios #MachineLearning meetup.com/Machine-Learni…

Dimitris Katsios (@dkatsios) 's Twitter Profile Photo

I'm experimenting with Keras 3.0 and was trying to use the API (compile(), fit() etc.) on a pytorch (nn.Module) model. Couldn't find exactly how to do it. E.g. take torchvision resnet18 make a keras.Model out of it and compile/fit it. Anyone how can point me to some code?

Philipp Schmid (@_philschmid) 's Twitter Profile Photo

A small, portable vector database powered by SQLite for on-device RAG? 🤯 sqlite-vec is a new vector search SQLite extension written entirely in C with no dependencies, MIT/Apache-2.0 dual licensed.   sqlite-vec queries: - 1 million 128-dimensional vectors in just 17ms - 500,000

A small, portable vector database powered by SQLite for on-device RAG? 🤯 sqlite-vec is a new vector search SQLite extension written entirely in C with no dependencies, MIT/Apache-2.0 dual licensed.  

sqlite-vec queries:
- 1 million 128-dimensional vectors in just 17ms
- 500,000
Andrew Ng (@andrewyng) 's Twitter Profile Photo

Announcing new aisuite capability: Easy function calling with LLMs! Function calling (tool use) is an important capability for agentic workflows and other LLM applications, but is cumbersome for developers to use (left column in image). Our open-source aisuite package simplifies

Announcing new aisuite capability: Easy function calling with LLMs! Function calling (tool use) is an important capability for agentic workflows and other LLM applications, but is cumbersome for developers to use (left column in image). Our open-source aisuite package simplifies