«[Intro to Deep Learning with PyTorch -- L2 -- N20] Cross-Entropy »[Tools] Package Your node.js Projects Into a Standalone Applications with pkg posted @2020-06-15 22:09Zhentiw阅读(341) 评论(0)编辑收藏举报 公告 昵称:Zhentiw
For the second example, where the line is described by 3x1+ 4x2 - 10 = 0, if the learning rate was set to 0.1, how many times would you have to apply the perceptron trick to move the line to a position where the blue point, at (1, 1), is correctly classified?
b+=learn_ratereturnW, b#This function runs the perceptron algorithm repeatedly on the dataset,#and returns a few of the boundary lines obtained in the iterations,#for plotting purposes.#Feel free to play with the learning rate and the num_epochs,#and see your results plotted below.deftrainP...
[Intro to Deep Learning with PyTorch -- L2 -- N15] Softmax function,TheSoftmaxFunctionInthenextvideo,we'lllearnaboutthesoftmaxfunction,whichistheequivalentofthesigmoidactivationfunction,butwhent
Gradient Descent: Familiarity with how gradient descent works and its limitations. Mathematics for Deep Learning: Basic calculus (derivatives) and linear algebra (vectors and matrices). Python Programming: Ability to implement neural networks using frameworks like PyTorch or TensorFlow. Pathological Curvatur...
In this introduction, I'd like to start with the very basics. We will ultimately be discussing deep learning, so we need to find out what that even means. To understand deep learning, we must first understand machine learning. Machine learning is the practice of using algorithms to analyz...
Therefore, we don't necessarily need any programming experience to understand the pseudocode. We have other great deep learning courses available that have a focus on coding, like our TensorFlow and PyTorch courses. We recommend taking these coding courses after learning the fundamentals in this ...
  ## Part 1: Intro to Deep Learning in Python -- TensorFlow and PyTorch TensorFlow...
Linear Algebra for Deep Learning(深度学习的线性代数) Fitting Neurons with Gradient Descent(梯度下降) Automatic Differentiation with PyTorch(PyTorch 中的自动微分) Logistic Regression and Multi-class Classification(逻辑回归) Multilayer Perceptrons(多层感知器) Regularization(神经网络的正则化方法) Feature Normaliz...
【 深度学习框架:PyTorch1.0现在和未来 】PyTorch 1.0: now and in the future(英文字幕)102 -- 19:55 App 【 Python编程 】Continuous Delivery in Python on a Massive Scale (英文)170 -- 35:28 App 【谷歌 I/O '18开发者大会 Tensorflow 】Distributed TensorFlow training(英文字幕)1387...