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https://www.ibm.com/blogs/bluemix/2015/04/tutorial-using-a-raspberry-pi-python-iot-twilio-bluemix/ #IoT#Python app with a #Raspberry_Pi and #Bluemix

http://www.aparat.com/v/0scM5 Irene Chen A Beginner's Guide to Deep Learning. What is #Deep_Learning ? It has recently exploded in popularity as a complex and incredibly powerful tool. This talk will present the basic concepts underlying deep learning in understandable pieces for complete beginners to #machine_learning.

http://www.aparat.com/v/Corus Advanced users #Deep_Learning, anyone who has followed #machine_learning over the past years has heard it. In this talk I will go past the hype and show what deep learning actually means and how one goes about solving complex machine learning task with a minimum amount of code, with the help of theano, an amazing python library for deep learning.

https://www.analyticsvidhya.com/blog/2016/08/deep-learning-path/?utm_content=bufferd56c5&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer #Deep_Learning, a prominent topic in #Artificial_Intelligence domain, has been in the spotlight for quite some time now. It is especially known for its breakthroughs in fields like Computer Vision and Game playing (Alpha GO), surpassing human ability. Since the last survey, there has been a drastic increase in the trends. (click here to check out the survey) Here is what Google trends shows us:

Dicio assistant Dicio is a free and open source#voice#assistant running on #Android. It supports many different skills and input/output methods, and it provides both speech and graphical feedback to a question. It interprets user input and (when possible) generates user output entirely on-device, providing privacy by design. It has multilanguage support, and is currently available in these languages: Czech, English, French, German, Greek, Italian, Polish, Russian, Slovenian, Spanish, Swedish and Ukrainian. Open to contributions :-D https://github.com/Stypox/dicio-android Download https://f-droid.org/packages/org.stypox.dicio https://github.com/Stypox/dicio-android/releases https://play.google.com/store/apps/details?id=org.stypox.dicio Skills Currently Dicio answers questions about: search: looks up information on DuckDuckGo (and in the future more engines) - Search for Dicio weather: collects weather information from OpenWeatherMap - What's the weather like? lyrics: shows Genius lyrics for songs - What's the song that goes we will we will rock you? open: opens an app on your device - Open NewPipe calculator: evaluates basic calculations - What is four thousand and two times three minus a million divided by three hundred? telephone: view and call contacts - Call Tom timer: set, query and cancel timers - Set a timer for five minutes current time: query current time - What time is it? navigation: opens the navigation app at the requested position - Take me to New York, fifteenth avenue media: play, pause, previous, next song Speech to text Dicio uses Vosk as its speech to text (#STT) engine. In order to be able to run on every phone small models are employed, weighing ~50MB. The download from here starts automatically whenever needed, so the app language can be changed seamlessly.

Russell Keith_Magee _ A tale of two #cellphones _ Python on #Android and #iOS _ PyCon 2016 It has been possible to write mobile applications in Python for a couple of years...

https://github.com/BVLC/caffe #Caffe is a #deep_learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.

Web fingerprinting is worse than I thought. #article#privacy @thedevs http://thedevs.link/chlPQn

http://www.kdnuggets.com/2017/09/essential-data-science-machine-learning-deep-learning-cheat-sheets.html#.WdGzWthHcEo.linkedin 30 Essential #Data_Science , #machine_learning & #Deep_Learning Cheat Sheets

https://www.analyticsvidhya.com/learning-paths-data-science-business-analytics-business-intelligence-big-data/learning-path-data-science-python/ Comprehensive learning path – #Data_Science in Python Journey from a Python noob to a Kaggler on Python So, you want to become a data scientist or may be you are already one and want to expand your tool repository. You have landed at the right place. The aim of this page is to provide a comprehensive learning path to people new to python for data analysis. This path provides a comprehensive overview of steps you need to learn to use Python for #data_analysis. If you already have some background, or don’t need all the components, feel free to adapt your own paths and let us know how you made changes in the path. You can also check the mini version of this learning path #Deep_Learning