Free annotation tools for Deep Learning, Computer Vision and Natural Language Processing tasks.
Extract the most important information from a CNN paper and learn how to code up the architecture. This time: "Xception: Deep Learning with Depthwise Separable Convolutions"
We are honored and excited to welcome Dimitris Katsios and Alisher Abdulkhaev to the MLT Board of Directors. Both have been part of our Computer Vision Team since 2018, they have been tirelessly supporting the community, teaching CNN architectures in numerous workshops in Tokyo and have always been an essential part of the organization. They … Continue reading NEW MEMBERS ON THE MLT BOARD OF DIRECTORS
We created a small repository linking to open Deep Learning and Reinforcement Learning lectures provided by MIT, Stanford University and UC Berkeley. ⚪ MIT 6.S191: Introduction to Deep Learning | 2020⚪ CS231n: CNNs for Visual Recognition, Stanford | Spring 2019⚪ CS224n: NLP with Deep Learning, Stanford | Winter 2019⚪ CS285: Deep Reinforcement Learning, UC Berkeley | … Continue reading AI CURRICULUM
As we are progressing with our tutorial, our group is already discussing potential applications. We're very excited to leave the neatly prepared course-datasets and dive into real world stuff. On a Thursday evening Yoovraj and I met and spontaneously wanted to start a small project. Since Yoovraj is into robotics, he always has an Arduino … Continue reading Trying Out New Things: Computer Vision and Robotics