机器学习 machine-learning-notes 返回
项目作者： roboticcam

项目描述 ：
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (1500+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(1500+页)和视频链接
高级语言： Jupyter Notebook
项目地址: git://github.com/roboticcam/machine-learning-notes.git
创建时间： 2018-02-15T15:42:33Z
项目社区：https://github.com/roboticcam/machine-learning-notes
开源协议：
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softmax_1650439185716.pdf
statistics_1650439186112.pdf
stochastic_matrices_1650439186214.pdf
variational_1650439186283.pdf
word_vector_1650439186423.pdf
random_measure_1650439185012.pdf
rbm_gan_1650439185114.pdf
recommendation_1650439185220.pdf
regression_1650439185350.pdf
reparameterization_1650439185582.pdf
mcts_1650439183618.pdf
neuralODE_Adjoint_1650439184018.pdf
neural_networks_1650439184184.pdf
non_parametrics_1650439184250.pdf
non_parametrics_extensions_1650439184355.pdf
optimization_1650439184474.pdf
particle_filter_1650439184565.pdf
policy_gradient_1650439184691.pdf
probability_1650439184835.pdf
em_1650439182974.pdf
gan_1650439183099.pdf
graph_cnn_1650439183169.pdf
introduction_monte_carlo_1650439183347.pdf
markov_chain_monte_carlo_1650439183463.pdf
deep_nlp2_1650439182130.pdf
dimension_reduction_1650439182434.pdf
dpp_1650439182559.pdf
dqn_1650439182667.pdf
dynamic_model_1650439182774.pdf
deep_nlp_1650439180574.pdf
cv_3d_research_1650439179841.pdf
deecamp_2019_1650439180319.pdf
cnn_beyond_1650439178486.pdf
cv_3d_foundation_1650439179239.pdf
GAN_1650439177993.pdf
bayesian_1650439178193.pdf
DeeCamp2018_Xu_final_1650439177625.pptx
AI_and_machine_learning_1650439174785.pdf
30_min_AI_1650439172104.pptx