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Venture capitalists have a reputation for wielding ruthless insights, judgements and criticisms of companies, tools and talent.
But how does a former-CTO-turned-VC assess companies? And now that he’s the one with the money, what does he look for - and expect to find - in a company’s engineering team?
In this post, I intend to break down how object detection is done using YOLO. Before fully understanding this hellish technological fiesta, you should know the difference between object classification, detection, and segmentation.
Image Reference: https://goo.gl/BPtB4f
Now that we have shown that it is easy to do standard NLP, next up is Deep Learning. As you can see, NLP, Machine Learning, Deep Learning, and more are all in your reach for building your own AI as a Service using tools from Cloudera. These can run in public or private clouds at scale. Now you can run and integrate machine learning services, computer vision APIs, and anything you have created in-house with your own Data Scientists. The YOLO pre-trained model will download the image to /tmp from the URL to process it. The Python 3 script will also download the GLUONCV model for YOLO3.
Using Pre-trained Model: