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“There is no single optimizer that dominates its competitors across all tasks.” Critics often call machine learning ‘glorified statistics’. There is some merit to the argument. The fundamental function of any machine learning model is pattern recognition, which relies on the principles of convergence; the methods of fitting data to the model. To that end,…
The post Does Deep Learning Suffer From Too Many Optimizers? appeared first on Analytics India Magazine.
Deep Learning is a subset of Machine learning. It was developed to have an architecture and functionality similar to that of a human brain.
The post Getting Started With Deep Learning Using TensorFlow Keras appeared first on Analytics India Magazine.
Gradient Descent is the most common optimisation strategy used in machine learning frameworks. It is an iterative algorithm used to minimise a function to its local or global minima. In simple words, Gradient Descent iterates overs a function, adjusting it’s parameters until it finds the minimum. Gradient Descent is used to minimise the error by…
The post A Lowdown On Alternatives To Gradient Descent Optimization Algorithms appeared first on Analytics India Magazine.