PDC4S:\IT\DATA SCIENCE AND MACHINE LEARNING\[Guvi.in] Deep Learning Course\DL#103 - Sigmoid Neuron\PDFs

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Lesson+10_+Learning+-+Learning+by+guessing.pdf73 KB12/12/2021 3:34 AM
Lesson+11_+Learning+-+Error+Surfaces+for+learning.pdf68 KB12/12/2021 3:34 AM
Lesson+12_+Learning+-+Mathematical+setup+for+the+learning+algorithm.pdf141 KB12/12/2021 3:34 AM
Lesson+13_+Learning+-+The+math-free+version+of+the+learning+algorithm.pdf225 KB12/12/2021 3:34 AM
Lesson+14_+Learning+-+Introducing+Taylor+Series.pdf162 KB12/12/2021 3:34 AM
Lesson+15_+Learning+-+More+intuitions+about+Taylor+series.pdf227 KB12/12/2021 3:34 AM
Lesson+16_+Learning+-+Deriving+the+Gradient+Descent+Update+Rule.pdf248 KB12/12/2021 3:34 AM
Lesson+17_+Learning+-+The+complete+learning+algorithm.pdf163 KB12/12/2021 3:34 AM
Lesson+18_+Learning+-+Computing+Partial+Derivatives.pdf170 KB12/12/2021 3:34 AM
Lesson+19_+Learning+-+Writing+the+code.pdf104 KB12/12/2021 3:34 AM
Lesson+20_+Sigmoid+-+Dealing+with+more+than+2+parameters.pdf221 KB12/12/2021 3:34 AM
Lesson+21_+Sigmoid+-+Evaluation.pdf146 KB12/12/2021 3:34 AM
Lesson+22_+Summary+and+take-aways.pdf130 KB12/12/2021 3:34 AM
Lesson+2_+Revisiting+limitations+of+perceptron+model.pdf1,413 KB12/12/2021 3:34 AM
Lesson+3_+Sigmoid+Model+Part+1.pdf42 KB12/12/2021 3:34 AM
Lesson+40_+Probability+Theory+Introduction.pdf176 KB12/12/2021 3:34 AM
Lesson+41_+Random+Variable+-+Intuition.pdf159 KB12/12/2021 3:34 AM
Lesson+42_+Random+Variable+-+Formal+Definition.pdf258 KB12/12/2021 3:34 AM
Lesson+43_+Random+Variable+-+Continuous+and+Discrete.pdf34 KB12/12/2021 3:34 AM
Lesson+44_+Probability+Distribution.pdf139 KB12/12/2021 3:34 AM
Lesson+45_+True+and+Predicted+Distribution.pdf36 KB12/12/2021 3:34 AM
Lesson+46_+Certain+Events.pdf36 KB12/12/2021 3:34 AM
Lesson+47_+Why+do+we+care+about+distributions_.pdf37 KB12/12/2021 3:34 AM
Lesson+48_+Information+Theory+Expectation.pdf223 KB12/12/2021 3:34 AM
Lesson+49_+Information+Content.pdf152 KB12/12/2021 3:34 AM
Lesson+4_+Sigmoid+Model+Part+2.pdf53 KB12/12/2021 3:34 AM
Lesson+50_+Entropy.pdf147 KB12/12/2021 3:34 AM
Lesson+51_+Relation+To+Number+Of+Bits.pdf157 KB12/12/2021 3:34 AM
Lesson+52_+KL-Divergence+and+Cross+Entropy.pdf69 KB12/12/2021 3:34 AM
Lesson+53_+Sigmoid+Neuron+and+Cross+Entropy.pdf156 KB12/12/2021 3:34 AM
Lesson+54_+Using+Cross+Entropy+With+Sigmoid+Neuron.pdf244 KB12/12/2021 3:34 AM
Lesson+55_+Learning+Algorithm+for+Cross+Entropy+loss+function.pdf168 KB12/12/2021 3:34 AM
Lesson+56_+Computing+partial+derivatives+with+cross+entropy+loss.pdf92 KB12/12/2021 3:34 AM
Lesson+57_+Code+for+Cross+Entropy+Loss+function.pdf76 KB12/12/2021 3:34 AM
Lesson+5_+Sigmoid+Model+Part+3.pdf99 KB12/12/2021 3:34 AM
Lesson+6_+Sigmoid+Model+Part+4.pdf36 KB12/12/2021 3:34 AM
Lesson+7_+Sigmoid+-+Data+and+Tasks.pdf40 KB12/12/2021 3:34 AM
Lesson+8_+Sigmoid+-+Loss+Function.pdf128 KB12/12/2021 3:34 AM
Lesson+9_+Learning+-+Intro+to+Learning+Algorithm.pdf35 KB12/12/2021 3:34 AM