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As of July 5th, 6:20 PM +08
New Feature Alert ⚡️
Evaluation Preview added into our training monitor tab to provide you with a deeper look at how your #deeplearing model is learning various features over time!
Identify images that the models have issues grasping as the training is happening 🔥 https://t.co/jZwpaIJP25
New Feature Alert ⚡️ We now support exporting your trained models in #TFLite and have created a dedicated interface to generate these conversions.
Moving forth, we will be working to support #PyTorch, ONNX, and more!
We are excited to announce that we've raised US$2.7 million for our Series Seed, led by @openspacevc 🚀
We remain dedicated to helping teams build AI breakthroughs. Let's democratize #deeplearning and #mlops together!
Our Thoughts → https://t.co/0MterStKvY https://t.co/raTI1zMJiW
Thanks for sharing this article @anebzt! Super interesting + useful💡We will share this in our next newsletter!
Thrilled to be part of your experiments - also glad the models work well with friends over at @streamlit and @huggingface 👋 https://t.co/B0aRHkFgfc
We are swiftly expanding our features to improve dev experience!
Now that the platform has reached a full end-to-end status, we can track your experiments from labelling to model performance.
Next up? Neural Network Deploy API 🌩 https://t.co/y3D9fSAHqt
IntelliBrush Early Access ends in a couple of weeks - just in time for our #ProductHunt launch!
A #deeplearning brush that requires only 2-3 clicks to generate masks labels for your dataset and requires no pre-training?
Try it out for yourself today ↓
Running sanity checks on your labelled dataset can be hard. Analyzing every image might not be feasible for all #deeplearning projects.
Introducing Metadata Queries - Search assets using expressions to validate your #dataset assumptions easily 🔦
Blog → https://t.co/XFM3g11eRs
Check out Datature Intellibrush! Announced during our Fall Webinar, we have made #annotation of complex much more efficient and accurate.
Requiring only 2-3 clicks, IntelliBrush uses #deeplearning to generate mask labels in less than a second ⚡️
Portal is the fastest way to load and visualize your #deeplearning models in your browser 🔮
We are all sick of wrangling a bunch of cv2 or matplotlib codes in collab to visually test CV models - especially on videos.
#OpenSource on https://t.co/BxRcpX3lCQ! Try it out today!
We have launched Portal on #ProductHunt! 👉https://t.co/ieZ7v0Rqwc
Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮 No more wrangling of cv2 or matplotlib just to check how your model is performing on videos or images!