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      "body": "Hi,\n<div class=\"text-justify\">\nIn my previous <a href=\"https://steemit.com/technology/@boostyslf/how-did-i-learn-machine-learning-part-3-implement-a-simple-neural-network-from-scratch-iv\">post</a>, I have presented you to derive the basic vectorized equations which are useful to create a simple neural network. I have mentioned those equations below.\n<br>\n<br>\n\neqn (10) : <code><b>Z = WX + B</b></code> \nHere the dimensions of <b>Ŷ</b> is 1\\*12288. In this way, we can write same equation which are quivalant to the equations we derived in previous posts. \neqn (11): <code><b>Ŷ = g(Z)</b></code> \neqn (12): <code><b>J = np.sum(-Ylog(Ŷ) - (1 - Y)log(1 - Ŷ))</b></code> \n(*here the <b>np.sum</b> means adding the all elimants in the matrix.*)\neqn (13): <code><b>∂W = (Ŷ - Y)X<sup>T</sup>/m</b></code> \neqn (14): <code><b>∂B = np.sum(Ŷ - Y)/m</b></code> \neqn (15): <code><b>W = W -α∂W</b></code> \neqn (16): <code><b>B = B -α∂B</b></code> \n\n<div class=\"pull-left\">https://cdn.steemitimages.com/DQmbeoQZcUEV1m9fXZL4Thj6iam4EMfrToxAk5caEBfVyM8/htchrs_id_yeah02.jpg</div>\nIn this post, I present you the code implementation according to the above equations. You can find the code here. In this blog, I am not going to explain each line because I have added the necessary comments to the <a href=https://github.com/KavinduZoysa/artificial-intelligence/blob/master/steemit/vectorization.py>code</a>. If you have any unclear point, please raise that. Also, I recommend you to implement the code on your own and compare it with my code.\n\nIn the next post, I will present you what is the learning rate and the effect of <b>learning rate</b> on the neural network.\n\nPlease feel free to raise any concerns/suggestions on this blog post. Let's meet in the next post.\n\nMy previous blogs,\n<a href=\"https://steemit.com/machine/@boostyslf/how-did-i-learn-machine-learning-step-1-create-the-coding-environment\">How did I learn Machine Learning : part 1 - Create the coding environment</a>\n<a href=\"https://steemit.com/ai/@boostyslf/how-did-i-learn-machine-learning-step-2-setup-conda-environment-in-pycharm\">How did I learn Machine Learning : part 2 - Setup conda environment in PyCharm</a>\n<a href=\"https://steemit.com/technology/@boostyslf/how-did-i-learn-machine-learning-part-3-implement-a-simple-neural-network-from-scratch-i\">How did I learn Machine Learning : part 3 - Implement a simple neural network from scratch I</a>\n<a href=\"https://steemit.com/technology/@boostyslf/how-did-i-learn-machine-learning-part-3-implement-a-simple-neural-network-from-scratch-ii\">How did I learn Machine Learning : part 3 - Implement a simple neural network from scratch II</a>\n<a href=\"https://steemit.com/technology/@boostyslf/how-did-i-learn-machine-learning-part-3-implement-a-simple-neural-network-from-scratch-iii\">How did I learn Machine Learning : part 3 - Implement a simple neural network from scratch III</a>\n<a href=\"https://steemit.com/technology/@boostyslf/how-did-i-learn-machine-learning-part-3-implement-a-simple-neural-network-from-scratch-iv\">How did I learn Machine Learning : part 3 - Implement a simple neural network from scratch IV</a>\n\nReferences:\n<a href=\"https://www.coursera.org/learn/neural-networks-deep-learning?specialization=deep-learning\">cousera</a>\n</div>\n\n</div>",
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