We know that our world is changing quickly but there are lot of concrete technology advances that you might not hear a lot about in the newspaper or on tv, that are nevertheless having a dramatic impact on our lives.
Some of these big new stories are related to the ANN(Artificial Neural Network) – a relatively new phenomenon in artificial intelligence research that’s driving all sorts of progress in many fields from entertainment to medicine. As a human, we discovered that we can build better models by throwing together many of these artificial neurons and making them work together in ways that are very like or biological thought process.
- Game playing and beyond: you may have heard recently that a computer was able to beat a human player in the game of “Go”, a game that’s significantly more complex than chess. A lot of us intuitively understand this is yet another step forward along the path toward stronger artificial intelligence.
- More precision in cancer treatment: Cancer is one of the most confounding diseases of the western medical lexicon – but now very few kinds of cancer research are being supported by artificial neural networks as scientists get close to breaking through to new ways of treating many different kinds of tumour.
- Progress in Neuro Science: ANN isn’t just useful in cancer research- the same principles can take all sorts of clinical data and refine it into more actionable forms. But there is a special relationship between ANN and neuroscience – because even as we are putting together these building blocks that simulate the human brain, we are learning more about how the human brain works- which is supporting new modern facilities to serve patients in new ways.
- AI ad personalized marketing: Another breakthrough that’s supported by artificial neural networks is the uncanny ability of marketers to figure out what a given consumer wants. You may have encountered this kind of thing in a website’s recommended engine. You also see ads, all this is driven by artificial neural network and machine learning algorithms that are able to make connections on their own rather than being driven by human decision-makers.
- Everyday Interfaces: A business is an organism and any business of significant size is going to need a bit of direction both day to day and over the long term.
- Business Intelligence: As soon as software became sufficiently advanced, vendors started building different enterprise software platforms to help businesses to automate everything that they used to do by hand. Rather than doing walk-throughs of facilities and trying to imagine what’s going to happen in the future, today’s leaders are increasingly looking at visual dashboards and seeing clearly, what they need to do to make the business work better.
- Implementing Artificial Neural Network training process in Python
- Introduction to Convolution Neural Network
- Introduction to Artificial Neural Network | Set 2
- A single neuron neural network in Python
- Applying Convolutional Neural Network on mnist dataset
- Introduction to Recurrent Neural Network
- Importance of Convolutional Neural Network | ML
- ML - Neural Network Implementation in C++ From Scratch
- Choose optimal number of epochs to train a neural network in Keras
- Implementation of Artificial Neural Network for AND Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for OR Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for NAND Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for NOR Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for XOR Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for XNOR Logic Gate with 2-bit Binary Input
- Implementation of neural network from scratch using NumPy
- Difference between Neural Network And Fuzzy Logic
- Deep Neural Network With L - Layers
- ANN - Implementation of Self Organizing Neural Network (SONN) from Scratch
- ANN - Self Organizing Neural Network (SONN)
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