机器学习代考高分91
这次Machine learning 考试涉及LDA linear discriminant analysis, gradient descent optimization, neural network, SVM, reinforcement learning, q-learning等等内容, 涉及范围非常广. 题量大, 时间紧, 取得高分非常不容易.
机器学习代写代考 machine learning
机器学习作为CS必修课程之一, 一般包括supervised learning监督学习, unsupervised learning 无监督学习和reinforcement learning(RL)增强学习3个大方向.
supervised learning通常需要学习linear regression, decision tree, SVM(support vector machine), logistic regression, naive bayes, random forest,
Neural Networks神经网络等内容.
深度学习deep learning是现在非常热门的方向, 需要学习CNN (convolution neural network), RNN (recurrent neural network)等网络架构. 知识点包括dropout, backpropagation, pooling, convolutional layer等. 深度学习现在已经广泛应用到计算机视觉 (computer vision) 和 NLP (自然语言处理).
unsupervised learning通常要学习principal component analysis (PCA), factor analysis, clustering algorithm such as K-means, EM (Expectation–maximization algorithm), GMM (gaussian mixture model)等.
reinforcement learning一般会学习Q-learning和Deep Q-learning.
机器学习代考高分
这次Machine learning考试涉及non-linear transformations, Support Vector Machines (SVM), Unsupervised Learning, Model Complexity等等. 最后成绩有90%以上, 非常好
IN2064 python 深度学习代写
IN2064 Practical Session 9 — Deep Learning 2 In this programming exercise your task is to use Tensorflow to classify reviews in the IMDB dataset. The possible labels are positive and negative, i.e. the task is binary classification. Fill in the required parts of the skeleton below. Train feed forward neural networks of different sizes
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python tensorflow深度学习代写 assignment 09
Programming assignment 09: Deep Learning In [1]: import numpy as np import matplotlib.pyplot as plt import tensorflow as tf %matplotlib inline Your Task In this notebook, the skeleton for learning a feed-forward neural network is given. Your task is to complete the functions where required. Submission Submit your notebook by January 6, 2019 as a .html file
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