https://arshadhs.github.io/tags/formula-sheet/Recent content in Formula Sheet on Arshad SiddiquiHugoen-ushttps://arshadhs.github.io/docs/ai/deep-learning/900-dnn-exam-formula-and-numerical-sheet/Mon, 01 Jan 0001 00:00:00 +0000https://arshadhs.github.io/docs/ai/deep-learning/900-dnn-exam-formula-and-numerical-sheet/<h1 id="dnn-formula-and-numerical-sheet"> DNN Formula and Numerical Sheet <a class="anchor" href="#dnn-formula-and-numerical-sheet">#</a> </h1> <p>This page consolidates the most useful Deep Neural Networks formulas and numerical patterns for revision.</p> <p>It is designed for preparation and should be used together with the topic pages.</p> <blockquote class="book-hint info"> <p><strong>Revision strategy:</strong><br> Do not only memorise formulas.</p> <p>For each formula, know:</p> <ol> <li>what each symbol means</li> <li>when to apply it</li> <li>how to substitute values carefully</li> <li>what the output shape or answer represents</li> </ol> </blockquote> <hr> <h1 id="1-artificial-neuron"> 1. Artificial Neuron <a class="anchor" href="#1-artificial-neuron">#</a> </h1> <h2 id="weighted-sum-"> Weighted Sum ☆ <a class="anchor" href="#weighted-sum-">#</a> </h2> <span style="color: blue;"> <span> \[ z = \sum_{i=1}^{n} w_i x_i + b \] </span> </span> <p>Vector form:</p>