Tensorflow is a powerful open-source software library for machine learning developed by researchers at Google Brain. It has many pre-built functions to ease the task of building different neural networks. Tensorflow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a single machine. TensorFlow provides a Python API, as well as a less documented C API. For this course, we will be using Python.

Schedule and Syllabus Unless otherwise specified the course lectures and meeting times are: Wednesday, Friday 3:30-4:20 Location: 200-219 This syllabus is subject to change according to the pace of the class.

He's been there for three weeks now -- though he is quick to point out that he was out of the office for one of them so it's really only been two weeks -- but that's not stopping Quartz from launching one of the Bot Studio's first experiments, a Twitter bot to help attendees of the NICAR conference. People going to #NICAR17 can ask a Twitter bot. Keefe says the Bot Studio, which is funded by a $240,000 grant from the Knight Foundation, will focus on two main areas: How bots and artificial intelligence can help journalists do their jobs better and how news consumers can use them to access news and information. Keefe joined Quartz after spending 16 years at WNYC. We spoke about the lessons he learned from public radio, his goals for the Bot Studio, and what it'll take for bots to catch on.

Do students learn as much when they read digitally as they do in print? For both parents and teachers, knowing whether computer-based media are improving or compromising education is a question of concern. With the surge in popularity of e-books, online learning and open educational resources, investigators have been trying to determine whether students do as well when reading an assigned text on a digital screen as on paper. The answer to the question, however, needs far more than a yes-no response. In my research, I have compared the ways in which we read in print and onscreen.

While understanding machine learning has never been easier, it helps to know how to get started on some of the latest tools and features that are available. In this hands-on workshop with Galvanize, you'll learn the very basics of machine learning via the language of Python. Our community of staff, students, and professional instructors will guide you through the elementary aspects of SciKit Learn, a popular machine learning library for the Python language. We will learn a bit more about matrices, develop a linear model on a real data set, and play around in the sandbox if we have time. You'll leave this session equipped to write your own scripts and feel more prepared to take the next steps on your path to understanding machine learning.

So, you have been thinking about picking up machine learning, but given the confusing state of the web you don't know where to begin? Or maybe you have finished the first 7 steps and are looking for some follow-up material, beyond the introductory? This post is the second installment of the 7 Steps to Mastering Machine Learning in Python series (since there are 2 parts, I guess it now qualifies as a series). If you have started with the original post, you should already be satisfactorily up to speed, skill-wise. If not, you may want to review that post first, which may take some time, depending on your current level of understanding; however, I assure you that doing so will be worth your effort.

Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement, emails, customer service, language translation, radiology reports, etc. There are a large variety of underlying tasks and machine learning models behind NLP applications. Recently, deep learning approaches have obtained very high performance across many different NLP tasks.

Time series forecasting is different from other machine learning problems. The key difference is the fixed sequence of observations and the constraints and additional structure this provides. In this mega Ebook written in the friendly Machine Learning Mastery style that you're used to, finally cut through the math and specialized methods for time series forecasting. Using clear explanations, standard Python libraries and step-by-step tutorials you will discover how to load and prepare data, evaluate model skill, and implement forecasting models for time series data.

After a year of delays, the UK government has finally shared its plans for a more prosperous digital Britain. Unveiled by the Department for Culture, Media and Sport (DCMS), the Digital Strategy report outlines steps to plug skills gaps and deliver free training to people who need it, pushing forward important UK technology sectors like AI and allowing UK companies to remain competitive as they come to terms with life after Brexit. One thing the report makes clear is that the government can't do it alone. It's enlisting the help of some of the UK's biggest employers and companies, which will offer four million free digital skills training "opportunities" to people who need them. Many are existing initiatives or have been expanded, but Google will offer five hours of free digital skills as part of its Garage initiative (unveiled late last year) and launch a summer programme in coastal towns, BT's Barefoot Computing Project will give teachers free extra computer science resources and O2 will continue to deliver online safety tips via its partnership with the NSPCC.

Following on from the updated Industrial Strategy announced in January and plans to boost the growth and support of Britain's artificial intelligence (AI) sector, the UK government outlined a brand new digital strategy to combat growing skills gap fears across the country. A Digital Skills Partnership with government, businesses and charities will see the creation of more than four million free digital skills training opportunities in the UK and includes education commitments from the likes of Lloyds Banking Group, Barclays and Google. Speaking to Silicon, several tech industry professionals have offered their reactions to the news, providing an insight into what the industry is thinking. "The Government's Digital Strategy is an exciting and welcome prospect at a time when UK businesses are facing a significant threat from digital disruption. To gain a competitive advantage, businesses should consider how they can use new technologies like artificial intelligence, even at this relatively early stage," she said.