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  • "Artificial Intelligence has a huge potential to create new jobs in India"

    BW CIO World met Jaap Zuiderveld, Vice President of Sales and Marketing at NVIDIA for Europe, Middle East, and India and Vishal Dupar, Managing Director of South Asia at NVIDIA to discuss NVIDIA's foray in Artificial intelligence and its market strategy.

    Source: Business World
    4092
  • Deep Voice 3: Ten Million Queries on a Single GPU Server

    Although much of the attention around deep learning for voice has focused on speech recognition, developments in artificial speech synthesis (text to speech) based on neural network approaches have been just as swift.

    Source: The Next Platform
    15603
  • The Devil Is in the Detail of Deep Learning Hardware

    To identify skin cancer, perceive human speech, and run other deep learning tasks, chipmakers are editing processors to work with lower precision numbers. These numbers contain fewer bits than those with higher precision, which require heavier lifting from computers.

    Source: Electronic Design
    8676
  • The Devil Is in the Detail of Deep Learning Hardware

    To identify skin cancer, perceive human speech, and run other deep learning tasks, chipmakers are editing processors to work with lower precision numbers. These numbers contain fewer bits than those with higher precision, which require heavier lifting from computers.

    Source: Electronic Design
    8079
  • Nvidia's CEO Jensen Huang Has a Long-Term Plan to Conquer AI

    Silicon Valley tends to fall in love with the new new thing. Chip maker Nvidia is the new old thing, an overnight success story years in the making that is having its moment and then some.

    Source: Fortune
    18210
  • Deep Learning - Past, Present, and Future

    There is a lot of buzz around deep learning technology. First developed in the 1940s, deep learning was meant to simulate neural networks found in brains, but in the last decade 3 key developments have unleashed its potential.

    Source: Kdnugget
    25959
  • TensorFlow: One of the Most Popular Framework of Machine Learning

    Deep Learning is a subset of Machine Learning and it works on the structure and functions of a human brain. It learns from the data that is structured and uses complex algorithms to train a neural net. This is a learning mechanism. Deep learning is a neural network somewhat looks like this there is something known as an input layer and then there is an output layer and in between there are a bunch of hidden layers so typically it would be at least one hidden layer and anything more than one hidden layer is known as a deep neural network so any neural network with more than three layers altogether right based known as a deep neural.

    Source: HOB
    11139
  • What's next to Deep Learning and why Machine Learning Experts are Turning to Deep Learning?

    Deep Learning is not very interpretable, and this makes it undesirable in cases where it is important to understand why a deep learning model is making certain predictions. Deep Learning will not replace traditional Machine Learning, they will live side by side. Deep Learning only adds the capability to bring low quality data into the fold, it self-learns rich features, and turns low quality data, like pixels and sound samples, into high quality features, which it then feeds into traditional machine learning. In fact, Deep Learning actually has normal machine learning as part of its pipeline.

    Source: HOB
    7827
  • How Large Amount of Data is managed by ML Algorithms?

    Some algorithms are better at learning with small data while others are preferable for large data. This fact can be understood rigorously through statistical learning theory. Intuitively, algorithm that chooses from a large or complex collection of models needs a larger data set to converge to a model that generalizes well to new data. Thus there is a trade-off between how complex model one wants to be able to learn and how much data and therefore also compute resources that one can provide.

    Source: HOB
    8769
  • List Of 6 Best Online Courses For Artificial Intelligence

    In this modern technological world it is very simple to get any kind of information It simply means you need not to go out in search of any kind of some information or pay any single penny to anyone for that. Just turn on the internet and google it.

    Source: HOB
    15498
  • Understanding Transfer learning: For deep learning

    In machine learning, huge data goes into training models. Many times the model becomes complex so the cost of model training increases at a higher rate. Models of machine learning which are complex can easily be prepared only if you have years of experience. The models are not created very efficiently if the machine learning and artificial intelligence engineers do not have a good experience. This is how to transfer learning is more significant for deep learning.

    Source: HOB
    16839
  • Few applications of deep learning for a beginner (using Python)

    Deep learning seems to be leading as in data science as it is more researched. There are many applications which can help you build a save future as predicted by the data scientist. Deep learning looks hard and intimidating. Applications like TensorFlow, Keras, GPU based computing might scare you but in reality, it is not too hard and its take time effort and time to follow, and applying these applications in regular problems is easy.

    Source: HOB
    29766
  • Kick Start With Machine Learning As Per Data Scientists Tips

    If you plan to start learning machine-learning models then you'll need a reasonably deep knowledge of math, spanning linear algebra, calculus, and statistics. But for beginners in the field, learning the basics of programming and getting to grips with a language like Python, which is commonly used for machine-learning tasks.

    Source: HOB
    19992
  • Revamping The Experience Of Big Data Analytics!

    According to a replacement, eBook OmniSci titled The OmniSci Extreme Analytics Platform: Revamping the expertise of huge data Analytics, all of them use the acute Analytics platform to form a sense of the huge amounts of vital, time period data they're perpetually accumulating.

    Source: HOB
    9471
  • Grab Few Programming Languages On the Peak for Machine Learning

    These are the top 10 machine learning which might lead you towards good skills and vast opportunities for your career. All these languages are the highly rated machine learning repositories.

    Source: HOB
    30162
  • Data Science Is The Pillar For An AI-Powered Enterprise

    For every business, data science is the foundation of enabling a successful transformation into an AI-powered enterprise.

    Source: HOB
    8271
  • Must Read: Courses that will Dive you Deep into the Deep Development of Deep Learning

    Learn deep, Acquire deep and Grab deep. Here you will get some courses which will take you to the way of deep learning, establish your career and gives you in-depth knowledge.

    Source: HOB
    6144
  • Intel brings up a platform which is optimized to run AI and ML models

    When we see that deep learning models are being trained, NVIDIA might bet full attention. However, Intel is not sitting quietly, just staring at the massive AI opportunity.

    Source: HOB
    6297
  • Learning the Top Artificial Intelligence Frameworks

    In this article, you will get to know some of the best frameworks to get you started with AI development.

    Source: HOB
    6846
  • Some Deep Learning courses to keep in mind

    Learn how to use Python and its popular libraries such as NumPy and Pandas, as well as the PyTorch Deep Learning library.

    Source: HOB
    3849
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