Neural Networks: Advantages and Applications

A human brain is not capable of solving complex data and cannot extract information from compound structures. To overcome this lack of...

Harnessing curiosity in Reinforcement Learning

Reinforcement learning is a specialized area of artificial intelligence where an algorithm applies independent and goal-oriented learning, based on rewards received from...

Top Artificial Intelligence Influencers To Follow in 2019

Yoshua Bengio: Yoshua BengioOCFRSC (born 1964 in Paris, France) is a Canadian computer scientist, most noted for his work on artificial neural networks and deep...

Top Machine Learning APIs That You Should Know

Here is a list of some of the important machine learning APIs for you to use. PREDICTION BASED

How Artificial intelligence can usher a new wave of Identity Verification services?

Artificial Intelligence is considered the next big thing when it comes to tech products and trends that will lead humanity to the...

Google Maps and AI: What’s The Future of Google’s Flagship Application?

When it comes to technological development in 2019, mobile comes first. Probably due to the fact that mobile traffic as a whole...

Regression using Tensorflow and partition of data for robust validation.

Again in the tutorial will use Gradient descent optimization algorithm. Additionally, we will divide our data set into three slices, Training, Testing,...

14 Great Articles To Read About TensorFlow

First Steps with TensorFlow: ToolkitGoogle + open-source = TensorFlow 9 Things You Should Know About TensorFlowDeep Learning with TensorFlow in Python TensorFlow Tutorial For...

Regression using Tensorflow and Gradient descent optimizer

Gradient descent is the most popular optimization algorithm, used in machine learning and deep learning. Gradient descent is iterative optimization algorithm for...

Artificial Intelligence – A Bitter-Sweet Symphony in Modelling

We have seen tremendous progress by artificial intelligence (AI) over the past decades. This progress, however, was not achieved steadily. There were...

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