Digests » 60
These deep learning interview questions cover many concepts like perceptrons, neural networks, weights and biases, activation functions, gradient descent algorithm, CNN (ConvNets), CapsNets, RNN, LSTM, regularization techniques, dropout, hyperparameters, transfer learning, fine-tuning a model, autoencoders, deep learning frameworks like TensorFlow, Keras etc.
Pluribus is the first AI bot capable of beating human experts in six-player no-limit Hold’em, the most widely-played poker format in the world. This is the first time an AI bot has beaten top human players in a complex game with more than two players or two teams.
Last month, I got an interesting request for a contract assignment on Upwork. An HR company called “FS consulting” tasked me with building an algorithm relating demographics to job performance. As a data scientist I was pretty intrigued because I had previously worked in the jobs industry, a start-up where I built candidate-job matching algorithms off of millions of data points.
It gives quite decent results by saving above 30% key strokes in most files, and close to 50% in some. We calculated key strokes saved by making a single (best) prediction and selecting it with a single key.
Big Data has become synonymous with Data engineering. But the line between Data Engineering and Data scientists is blurring day by day. At this point in time, I think that Big Data must be in the repertoire of all data scientists.