deep-learning-keras-euroscipy2016 – # Deep Learning with Keras
Goal of this Tutorial
- Introduce main features of Keras
- Learn how simple and Pythonic is doing Deep Learning with Keras
- Understand how easy is to do basic and advanced DL models in Keras;
- Examples and Hand-on Excerises along the way.
Do you write programs in Python? You should be using attrs.
Why, you ask? Don’t ask. Just use it.
Okay, fine. Let me back up.
I love Python; it’s been my primary programming language for 10+ years and despite a number of interesting developments in the interim I have no plans to switch to anything else.
But Python is not without its problems. In some cases it encourages you to do the wrong thing. Particularly, there is a deeply unfortunate proliferation of class inheritance and the God-object anti-pattern in many libraries.
One cause for this might be that Python is a highly accessible language, so less experienced programmers make mistakes that they then have to live with forever.
But I think that perhaps a more significant reason is the fact that Python sometimes punishes you for trying to do the right thing.
The “right thing” in the context of object design is to make lots of small, self-contained classes that do one thing and do it well. For example, if you notice your object is starting to accrue a lot of private methods, perhaps you should be making those “public” methods of a private attribute. But if it’s tedious to do that, you probably won’t bother.
Source: Deciphering Glyph :: The One Python Library Everyone Needs
Machine learning could train software to spot verbal tics associated with schizophrenia, depression, and bipolar disorder.
Source: How Artificial Intelligence Could Help Diagnose Mental Disorders – The Atlantic
Why Python is awesome and you should at least give it a try.
My first encounter with Python was a part of the introductory course to programming. Well, I actually played with it on my own before, so I already was familiar with its syntax when the course began, but I didn’t do any real project in it before that course. Even though I thought it’s a great language to introduce people to programming, I wasn’t a big fan of it. It’s not that I disliked the language, it was more of a “meh” attitude. The reason was simple: there was “too much magic”. Coming from a background of languages such as C an Java, which are a lot more explicit in terms of what’s going on under the hood, Python was the complete opposite of that.
Another issue was that Python seemed a lot less structured: writing large, complex programs seemed to be a tougher task to achieve than, for example in Java, where you have some strict rules when it comes to the structure of the program (for instance the one public class per file rule), Python on the other hand, gives you a lot more freedom in such things.
Another thing is strict typing and debugging: since Python is an interpreted language, finding bugs wasn’t as easy: if you have a syntax error in C, the program will simply not compile, on the other hand, in interpreted languages, the problem might go unnoticed for quite some time, until the execution reaches that particular line of code. Trying to pass a string where an integer is expected?
cc will go crazy at you, while Python’s interpreter won’t mind at all (there are some tool that address that problem though, like mypy, but I’m talking about vanilla Python). What I just mentioned here is a general downside of interpreted languages and are not exclusive or particular to Python, but those were some of the main reasons of my initial attitude towards it.
Source: Why You Should Learn Python – G’d Up Code
If a brain-stimulation gadget catches on, expect controversy over “brain doping”
Source: Olympic Athletes Are Electrifying Their Brains, and You Can Too – IEEE Spectrum
Op-Ed Columnist Hillary Health Shocker! Think the Clinton-Trump Race Will Be a Landslide? Hold Your Horses Hillary Clinton’s 15,000 New Emails to Get Timetable for Release Liberal, Moderate or Conservative? See How Facebook Labels You New York 101 Why Are New York City’s Streets Always Under Construction? The New Health Care The EpiPen, a Case Study in Health Care System Dysfunction Zika, a Formidable Enemy, Attacks and Destroys Parts of Babies’ Brains Abu Zubaydah, Tortured Guantánamo Detainee, Makes Case for Release Andrea Tantaros of Fox News Claims Retaliation for Sex Harassment… Feature Fractured Lands: How the Arab World Came Apart Feature Where the Death Penalty Still Lives Who Will Be President? Travel Tips You Can Save on Airfare (If You Know the Tricks) Op-Ed Columnist Why America’s Leadership Fails Fixes Putting the Power of Self-Knowledge to Work Editorial The Fake $400 Million Iran ‘Ransom’ Story Delicate Mix of Compassion and Politics as Obama Visits Louisiana Flood Victims Steven Hill, Who Starred on ‘Law & Order’ and ‘Mission: Impossible,’ Dies at 94 Tucson Becomes an Unlikely Food Star Economic Trends The Housing Market Is Finally Starting to Look Healthy Loading…TrendingAdvertisementBook Review | NonfictionOverselling A.D.H.D.: A New Book Exposes Big Pharma’s Role
Source: Overselling A.D.H.D.: A New Book Exposes Big Pharma’s Role – The New York Times
Okay folks. Time’s up. It’s too late to say that Python’s packaging ecosystem terrible any more. I’m calling it.
Python packaging is not bad any more. If you’re a developer, and you’re trying to create or consume Python libraries, it can be a tractable, even pleasant experience.
I need to say this, because for a long time, Python’s packaging toolchain was … problematic. It isn’t any more, but a lot of people still seem to think that it is, so it’s time to set the record straight.
If you’re not familiar with the history it went something like this:
Source: Deciphering Glyph :: Python Packaging Is Good Now
Some people begin to work or tackle personal tasks before sunrise, aiming to find focus before distractions begin in the standard morning rush.
Source: Why 4 a.m. Is the Most Productive Hour – WSJ
TL;DR Motivated by a friend, we’ll share bits of our experience during the Olympic Games Rio 2016. Before starting, I would like to clarify that Globo.com only had rights for streaming the content …
Source: More than 400 Tb of live streaming were transferred during the Olympic Games Rio 2016 | Leandro Moreira
Social media APIs and their rate limits have not been nice to me recently, especially Instagram. Who needs it anyway? Sites are increasingly getting smarter against scraping / data mining attempts. AngelList even detects PhamtomJS (have not seen other sites do this). But if you are automating your exact actions that happen via a browser, […]
Source: I Don’t Need No Stinking API – Web Scraping in 2016 and Beyond