Machine Learning

AI learning evolution

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Overview UC Berkeley has open sourced the world's largest and most diverse self-driving dataset It contains 100,000 video sequences, each approximately 40 seconds long and in 720p quality This dataset is 800 times bigger than Baidu's ApolloScape! Introduction Self-driving cars are on the verge of transforming the way we
A visual introduction to machine learning-Part II The goal of modeling is to approximate real-life situations by identifying and encoding patterns in data. Models make mistakes if those patterns are overly simple or overly complex. In Part 1, we created a model that distinguishes homes in San Francisco from those in New York.
We are happy to announce the release of the latest version of ML-Agents: v0.4. It contains a number of features, which we hope everyone will enjoy. It includes the option to train your environments directly from the editor, rather than as built executables, making iteration time much quicker.
Object detection is a domain that has benefited immensely from the recent developments in deep learning. Recent years have seen people develop many algorithms for object detection, some of which include YOLO, SSD, Mask RCNN and RetinaNet. For the past few months, I've been working on improving object detection at a research lab.
Tom Silver | About Me | Favorite Papers | Blog By Tom Silver A friend of mine who is about to start a career in artificial intelligence research recently asked what I wish I had known when I started two years ago. Below are some lessons I have learned so far.
There are a lot of neat things going on in deep reinforcement learning. One of the coolest things from last year was OpenAI and DeepMind's work on training an agent using feedback from a human rather than a classical reward signal.
For quite a long time, a common opinion in academic world was that machine achieving human master performance level in the game of Go was far from realistic. It was considered a 'holy grail' of AI - a milestone we were quite far away from reaching within upcoming decade.
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