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Artificial Intelligence

IT leaders’ pragmatism will be the antidote to AI scaremongering

IT leaders' pragmatism will be the antidote to #AI dystopia:  #MachineLearning #AI4socialgood

  • Every development in AI is portrayed as the forerunner to Skynet from the Terminator movies, or something from Blade Runner, Westworld or another vision of a future ruled by robot overlords.
  • Paypal founder and billionaire entrepreneur Elon Musk joined in, warning that AI represented the greatest threat to mankind.
  • Sadly, we’re probably going to have to get used to this for a few years yet, until AI becomes more mainstream, creates as many jobs as it eliminates, and starts to deliver huge benefits to businesses and society – much like new technologies have for the last 50 years.
  • We are, in many ways, starting into an age where what was once science fiction will become a reality – but just because sci-fi writers realised that dystopian visions sell more books than utopian dreams, we’ve become culturally conditioned to the idea that too much new technology is a bad thing.
  • For IT professionals, your job is to understand and explain what AI and other emerging technologies can bring to your business and your customers – and to deliver the enormous potential on offer.

Clearly we are going through the phase in the development of artificial intelligence (AI) technology where rationality and reasoned debate are replaced by science-fiction scaremongering and …

The post IT leaders’ pragmatism will be the antidote to AI scaremongering appeared first on Artificial Intelligence.



Large Scale Machine Learning for Payment Fraud Prevention Recorded at:

How advanced #machinelearning algorithms are applied at @PayPal for #fraud prevention. 

?

  • Venkatesh Ramanathan is a senior data scientist at PayPal where he is working on building state-of-the-art tools for payment fraud detection.
  • Venkatesh has worked on various problems in the areas of Anti-Spam, Phishing Detection, and Face Recognition.
  • Data Science is an emerging field that allows businesses to effectively mine historical data and better understand consumer behavior.
  • This type of scientific data management approach is critical for any business to successfully launch its products and better serve its existing markets.

Venkatesh Ramanathan presents how advanced machine learning algorithms such as Deep Learning and Gradient Boosting are applied at PayPal for fraud prevention.

The post Large Scale Machine Learning for Payment Fraud Prevention Recorded at: appeared first on Artificial Intelligence.



AI Superstar Andrew Ng Is Democratizing Deep Learning With A New Online Course

#AI hero @AndrewYNg is #democratizing #deeplearning w/ new online course
in @FastCompany

  • That’s the vision of Andrew Ng, a founder of the Google Brain deep learning project, and former head of AI at Baidu–a position he left in March–who is today announcing a set of five interconnected online courses on the subject.
  • “Today, if you want to learn deep learning, there are lots of people searching online, reading [dozens of] research papers, reading blog posts, and watching YouTube videos,” Ng tells Fast Company.
  • As Ng sees it, getting to an AI-powered economy is going to take the work of much more than any one, or even several companies.
  • “I hope we can build an AI-powered future that provides everyone affordable healthcare, accessible education, inexpensive and convenient transportation, and a chance for meaningful work for every man and woman,” Ng says in his announcement, which is the first from his newly created company, deeplearning.ai.
  • Ng is aware that many people are still confused by AI, often getting bogged down in the different subspecialties, and lingo that can easily be misused.

The founder of Google Brain and former head of Baidu’s AI efforts wants to train a giant new workforce to help make “AI the new electricity.”

The post AI Superstar Andrew Ng Is Democratizing Deep Learning With A New Online Course appeared first on Artificial Intelligence.



I blame the parents – AI needs to be raised right

I blame the parents – #AI needs to be raised right

  • Nexus CX, a pioneer in AI, is getting properly up close and personal.
  • In SU’s pilot stages, men who thought they were talking to a bot responded more openly than those who were told they were speaking with a human at the other end.
  • Nexus CX are working with Amazon’s Alexa, recording Trainor’s friend, documenting his memories and thoughts, helping to test a virtual counterpart and robot avatar that will speak based on collected patterns of speech.
  • It’ll console people in a way that humans can’t.
  • And when you think of the great technological advancements of the past decade, one creation stands head and shoulders above the rest: the iPhone.

Apparently, artificial intelligence is going to take over our lives, our jobs, our minds even and not necessarily in a good way. It’s inevitable.

The post I blame the parents – AI needs to be raised right appeared first on Artificial Intelligence.



Learn how AI is changing the application development landscape

Learn how #AI is changing the #application #development landscape. Get the report:

  • Is AI on your software development roadmap?
  • With technologies like advanced machine learning, deep learning, natural language processing, and business rules, AI is poised to disrupt both how developers build applications and the nature of those applications.
  • The risks—unrealistic expectations, integration with traditional applications, and more—can’t be ignored as your organization strives for the rewards of an accelerated development cycle and a new generation of self-learning applications.
  • Uncover this shifting digital landscape and how your business can take advantage of it in the Forrester Research report, “How AI Will Change Software Development And Applications.”
  • Fill out the form at right to read the free report.

Learn how AI is changing the application development landscape

The post Learn how AI is changing the application development landscape appeared first on Artificial Intelligence.



Accenture Business Journal for India – Vol. 3

Fuel your #IntelligentAutomation journey with a core #AI competency #ABJI2017

  • From smart connected plants and insight-driven enterprises to Blockchain-enabled services, Indian enterprises want to take digital to the next level.
  • How should they leverage the evolution of digital technology-especially in artificial intelligence-to build new business models, new products and services or enter new markets?
  • This edition of the Accenture Business Journal for India reveals the secret sauce for digital success across industries-from telecom, consumer packaged goods to manufacturing.
  • Take a deep dive and learn how to Lead in the New and avoid digital oblivion.

Accenture Business Journal for India – Vol. 3

The post Accenture Business Journal for India – Vol. 3 appeared first on Artificial Intelligence.



GitHub

Official #TensorFlow implementation of Dense Transformer Networks

  • In this work, we propose Dense Transformer Networks to apply spatial transformation to semantic prediction tasks.
  • The third and fourth rows are the segmentation results of U-Net and DTN, respectively.
  • max_epoch: how many iterations or steps to train

    test_step: how many steps to perform a mini test or validation

    save_step: how many steps to save the model

    summary_step: how many steps to save the summary

    sampledir: where to store predicted samples, please add a / at the end for convinience

    model_name: the name prefix of saved models

    test_epoch: which step to test or predict

    network_depth: how deep of the U-Net including the bottom layer

    class_num: how many classes.

  • We have conv2d for standard convolutional layer, and ipixel_cl for input pixel convolutional layer proposed in our paper.
  • We have deconv for standard deconvolutional layer, ipixel_dcl for input pixel deconvolutional layer, and pixel_dcl for pixel deconvolutional layer proposed in our paper.

Contribute to dtn development by creating an account on GitHub.

The post GitHub appeared first on Artificial Intelligence.



GitHub

  • This is a pure Tensorflow implementation of Deep Photo Styletransfer, the torch implementation could be found here

    This implementation support L-BFGS-B (which is what the original authors used) and Adam in case the ScipyOptimizerInterface incompatible when Tensorflow upgrades to higher version.

  • is to generate segmented intermediate result like torch file neuralstyle_seg.
  • uses this intermediate result to generate final result like torch file deepmatting_seg.
  • Run to see a list of all options

    This repository doesn’t offer image segmentation script and simply use the segmentation image from the torch version.

  • Here are more results from tensorflow algorithm (from left to right are input, style, torch results and tensorflow results)

    If you find this code useful for your research, please cite:

    Feel free to contact me if there is any question (Yang Liu lyng_95@zju.edu.cn).

deep-photo-styletransfer-tf – Tensorflow (Python API) implementation of Deep Photo Style Transfer

The post GitHub appeared first on Artificial Intelligence.



Data Science As A Career Change – My Story as a Video Interview

MT @_data_mania: Video interview~
#DataScience as #career change
#WomenInTech #AI

  • If you’re like most people who work with data on a regular basis, you’re probably hearing about data science as a career change option and wondering “Is data science right for me?
  • Although I can’t answer those lingering questions for you – I can tell you my experience, as a person who approached data science as a career change.
  • In this exclusive premier interview for LinkedIn Learning, I discuss how I transitioned myself from an Environmental Engineer to a Data Scientist.
  • There’s a lot covered in this lively 30-minute session; And if you’re considering data science as a career change, watching it should help you get a better idea what to expect, and hopefully a little inspiration to ignite your passion.
  • If you liked this video and want to learn more about how to make the transition into data science as a career change, then be sure to check out my LinkedIn Learning / Lyndas training courses here.

If you’re like most people who work with data on a regular basis, you’re probably hearing about data science as a career change option and wondering…

The post Data Science As A Career Change – My Story as a Video Interview appeared first on Artificial Intelligence.



Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data

Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data @kojouharov

  • To make things more interesting and give context, I added descriptions and/or excerpts for each major topic.This is the most complete list and the Big-O is at the very end, enjoy…If you like this list, you can let me know here.Neural NetworksNeural Networks Cheat SheetNeural Networks GraphsNeural Networks Graphs Cheat SheetNeural Network Cheat SheetMachine Learning OverviewMachine Learning Cheat SheetMachine Learning: Scikit-learn algorithmThis machine learning cheat sheet will help you find the right estimator for the job which is the most difficult part.
  • The flowchart will help you check the documentation and rough guide of each estimator that will help you to know more about the problems and how to solve it.Machine Learning Cheat SheetMACHINE LEARNING : ALGORITHM CHEAT SHEETThis machine learning cheat sheet from Microsoft Azure will help you choose the appropriate machine learning algorithms for your predictive analytics solution.
  • First, the cheat sheet will asks you about the data nature and then suggests the best algorithm for the job.MACHINE LEARNING ALGORITHM CHEAT SHEET If you like this list, you can let me know here.
  • Data Wrangling Cheat SheetPandas Data Wrangling Cheat SheetData Wrangling with dplyr and tidyrData Wrangling with dplyr and tidyr Cheat SheetData Wrangling with dplyr and tidyr Cheat SheetScipySciPy builds on the NumPy array object and is part of the NumPy stack which includes tools like Matplotlib, pandas and SymPy, and an expanding set of scientific computing libraries.
  • Data VisualizationData Visualization Cheat Sheetggplot cheat sheetPySparkBig-OBig-O Algorithm Cheat SheetBig-O Algorithm Complexity ChartBIG-O Algorithm Data Structure OperationsBig-O Array Sorting AlgorithmsAbout StefanStefan is the founder of Chatbot’s Life, a Chatbot media and consulting firm.

Over the past few months, I have been collecting AI cheat sheets. From time to time I share them with friends and colleagues and recently I have been getting asked a lot, so I decided to organize and…

The post Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data appeared first on Artificial Intelligence.



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