Bidirectional LSTMs are an extension of traditional LSTMs that can improve model performance on sequence classification problems. In problems where all timesteps of the input sequence are available, Bidirectional LSTMs train two instead of one LSTMs on the input sequence. The first on the input sequence as-is and the second on a reversed copy of the input sequence. This can provide additional context to the network and result in faster and even fuller learning on the problem. In this tutorial, you will discover how to develop Bidirectional LSTMs for sequence classification in Python with the Keras deep learning library.

As such, it was only natural for them to decide to enroll in the Japanese language and culture course that Makati Science High School has been offering ninth- and 10th-graders over the past few years. "My reason for joining the nihongo (Japanese-language) class was initially for anime. But halfway through, I realized I can use it to be able to experience going to Japan," 16-year-old Franza, who took the elective course for two years starting in 2015, said in a recent interview. Chee, who is a year younger than Franza, said, "One of my life goals (includes) watching anime without subtitles. The Filipino Department of Education started offering the Japanese language and culture program to high school students in 2009, together with Spanish and French, to prepare young Filipinos for both local and international opportunities that would require communicative competence in a second foreign language, after English. Mandarin Chinese and German have subsequently been added. The foreign language programs are offered in selected schools across the country, with Japanese taught in 38 schools, mostly in Manila. So far, more than 3,000 students, nearly all avid viewers of Japanese anime, have enrolled in the Japanese program while in grades nine and 10. "We have to recognize the fact that the globe is getting smaller and smaller," Education Secretary Leonor Briones said of the program's relevance. Many students want to go on to further their studies, both at the undergraduate and graduate levels, and Japan is one of the preferred overseas destinations, given the availability of many scholarships to study there, the secretary said. "So it helps if they take lessons.

Are you hungry to learn new skills? Don't know, what are the best selling online courses on Development? I am here to assist you to grab top courses at lower price. If pricing was the bar to learn, this is no more an issue. Since Udemy is offering new coupons and deals with huge discounts in week and month.

R language is the world's most widely used programming language for statistical analysis, predictive modeling and data science. It's popularity is claimed in many recent surveys and studies. R programming language is getting powerful day by day as number of supported packages grows. Some of big IT companies such as Microsoft and IBM have also started developing packages on R and offering enterprise version of R. What is R? R is a free language and environment for statistical computing and graphics. You can perform a variety of tasks using R language.

When scholars explore new ideas, it seems instinctive to share their thinking. Last year computer science professors Joseph Halpern and Bart Selman became co-principal investigators for a nationwide project to ensure that robots and artificial intelligences (AIs) will act in ways beneficial to humans. "We thought we should get undergrads involved in thinking about these ideas," Selman said. Thus was born a new course, CS 4732, Ethical and Social Issues in AI, about how robots and artificial intelligences may change our world, and what we ought to be doing about it. "These undergrads may be directly involved in developing the software behind these systems," Selman added, noting that many may go on to jobs with Google, Tesla and other major players.

Philip, who was underweight when he arrived, says to Adam, who is overweight: "I'm worried that you're not eating healthily. I noticed you've been skipping dinner." Adam is meant to repeat back to Philip what he heard him say the problem is. He mumbles, barely audible, and can't seem to remember what he's just been told. He's unable to focus, and the air is thick with reluctance and embarrassment.

Welcome to part four of Learning AI if You Suck at Math. (Be sure to check out the other articles in this series: 1, 2, 3, 4, 5, 6, and 7.) Maybe you've downloaded TensorFlow and you're ready to get started with some deep learning? But then you wonder: What the hell is a tensor? Perhaps you looked it up on Wikipedia and now you're more confused than ever. Maybe you found this NASA tutorial and still have no idea what it's talking about? The problem is most guides talk about tensors as if you already understand all the terms they're using to describe the math. I hated math as a kid, so if I can figure it out, you can too!

After my first post on Anomaly Detection for Time Series post, I would like to continue presenting what I did during the course at for the Data Science for IoT Course at Department of Continued Education of the University of Oxford with Ajit Jaokar. In line with what I wrote previously, this second post will be about predictive maintenance. The post will conclude the initial exploration of the topics I covered at Oxford. When researching materials to cover this course, I had a general idea of what to look for. Having worked already in industrial environments, I had a good idea of what predictive maintenance should be and how it could be used.

Due to the recent achievements of artificial neural networks across many different tasks (such as face recognition, object detection and Go), deep learning has become extremely popular. This post aims to be a starting point for those interested in learning more about it. If you already have a basic understanding of linear algebra, calculus, probability and programming: I recommend starting with Stanford's CS231n. The course notes are comprehensive and well-written. The slides for each lesson are also available, and even though the accompanying videos were removed from the official site, re-uploads are quite easy to find online.

When it launched, the Udacity Artificial Intelligence Nanodegree program became a kind of landmark in this history of AI. There was no precedent for the program's groundbreaking combination of content, platform, partners, and services. That simply did not exist before. The first term of students to enroll and start the program got to experience something genuinely new. They were risk-takers in every sense of the term.