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Neural Network Machine Learning Algorithm From Scratch in Python
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Demystifying the so-called Black Box of Neural Network
Introduction:
Do you really think that a neural network is a block box? I believe, a neuron inside the human brain may be very complex, but a neuron in a neural network is certainly not that complex.
It does not matter, what software you are developing right now, if you are not getting up to speed on machine learning…you lose. We are going to an era where one software will create another software and perhaps automate itself.
In this article, we are going to discuss how to implement a neural network Machine Learning Algorithm from scratch in Python. This means we are not going to use deep learning libraries like TensorFlow, PyTorch, Keras, etc.
Note that this is one of the posts in the series Machine Learning from Scratch. You may like to read other similar posts like Gradient Descent From Scratch, Linear Regression from Scratch, Logistic Regression from Scratch, Decision Tree from Scratch.
You may like to watch a video version of this article for a more detailed explanation…
General Terms:
Let us first discuss a few statistical concepts used in this post.
Dot Product of Matrix: Dot product of two matrices is one of the most important operations in deep learning. In mathematics, the dot product is a mathematical operation that takes as input, two equal-length sequences of numbers, and outputs a single number.
Not all matrices are eligible for multiplication. To carry out the dot product of two matrices, The number of…
