The Los Angeles Police Department deployed its controversial robot dog during a standoff with an armed man on a Metro bus Wednesday -- only to realize the person was asleep. Police responded to the busy intersection of Melrose and Western avenues in Hollywood just before 4 a.m. after receiving a report of a man with a gun on a bus, Officer Melissa Ohana said. The LAPD has since confirmed that the robot dog had been used before. A passenger had informed the bus driver about the armed man, and the driver contacted police. The driver pulled the bus to the side of the road and passengers safely got out, while the man stayed on board.

A loan is money borrowed to someone (the debtor) with the intent to pay back at an agreed date. Ideally, things should go as planned but when the debtor fails to pay the person they borrowed the loan from (the creditor), the debtor is said to have defaulted on the loan. It is then important for creditors/loan companies to know/predict if a certain debtor will default or not. This is a problem that machine learning solves, this is a classification machine learning problem. As with every machine learning problem, data is the major ingredient in solving it.

In the world of machine learning, long short-term memory networks (LSTMs) are a powerful tool for processing sequences of data such as speech, text, and video. The recurrent nature of LSTMs allows them to remember pieces of data that they have seen earlier in the sequence. Conceptually, this is easier to understand in the forward direction (i.e., start to finish), but it can also be useful to consider the sequence in the opposite direction (i.e., finish to start). Joe likes blank, especially if they're fried, scrambled, or poached. In the forward direction, the only information available before reaching the missing word is "Joe likes blank ", which could have any number of possibilities.

In the world of machine learning, long short-term memory networks (LSTMs) are a powerful tool for processing sequences of data such as speech, text, and video. The recurrent nature of LSTMs allows them to remember pieces of data that they have seen earlier in the sequence. Conceptually, this is easier to understand in the forward direction (i.e., start to finish), but it can also be useful to consider the sequence in the opposite direction (i.e., finish to start). Joe likes blank, especially if they're fried, scrambled, or poached. In the forward direction, the only information available before reaching the missing word is "Joe likes blank ", which could have any number of possibilities.

Reviewers were granted a mere week to play a title most players will enjoy over the course of several weeks or months. That's not a good way to assess a title of this scope. You might overhear a piece of dialogue, or find a handwritten note, that changes your read on the game's political valence, for better or worse. You might love how the cars handle, or the fishing minigame or hunting for treasure. But these are all obstacles to reviewing a game that could take 40-plus hours to beat.