Deep learning

Deep learning and Machine Learning can be confused, but there is a difference. Do you know it? Keep reading to get the answer!

Artificial neural networks (ANNs) are the cornerstone of Deep Learning algorithms. The name and the architecture are adopted from the human brain's neural network. ANNs are designed to simulate human reasoning based on how neurons communicate. ANNs contain a set of artificial neurons connected.

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As a beginner, jumping into a new machine learning project can be overwhelming. The whole process starts with picking a data set, and second of all, study the data set in order to find out which machine learning algorithm class or type will fit best on the set of data.

Despite successful research and developments in lab settings, deep learning has yet to reach its potential in real-world deployments.

Data science organizations face three common challenges as they operationalize and scale their machine learning models.

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Workers are warned: “They’ll never admit it in public, but many of your bosses want machines to replace you as soon as possible.”

In the light of India facing double whammy of communicable and non-communicable diseases, Artificial Intelligence (AI), an emerging technology, is being hailed for its immense transformational possibilities in providing an enriched healthcare experience to people at large.