摘要：
1. Different types of neurons Linear neurons Binary threshold neurons Recitified linear neurons sigmoid neurons Stochastic binary neurons 2. Reinforce 阅读全文
摘要：
1. Pandas plotting Output: 2. Seaborn Output: joint plots Second example Third example Output: 阅读全文
摘要：
1. Subplots Output: 2 .Histogram Output: Output： 3. Box plots Output: 4. Heartmap Output: 5. Animation Output: 6. Interactivity Mousing clickigng Outp 阅读全文
摘要：
1. Matplotlib Backend Layer Deals with th e rendering of plots to screen or files In jupyter notebooks, we use the inline backend Artist Layer Contain 阅读全文
摘要：
1. Visualization wheel dimensions Abstraction - Figuration boxes and charts(abstraction) or real-world physical objects(figuration) Functionality - De 阅读全文
摘要：
1. Reading csv File 2. Dates and times demo # Numpy introduction Output 1 [1 2 3] 2 (2L, 3L) 3 4 The use of arange: 5 [ 0 2 4 6 8 10 12 14 16 18 20 22 阅读全文
摘要：
1. Hierarchical clustering Avoid choosing number of clusters beforehand Dendrograms help visualize different clustering granularities (no need to reru 阅读全文
摘要：
1. Mixed membership model This model wants to discover a set of memberships In contrast, cluster models aim at discovering a single membership In clus 阅读全文
摘要：
1. Probabilistic clustering model (k-means) Hard assignments do not tell the full story, capture the uncertainty k-means only considers the cluster ce 阅读全文
摘要：
,1.One nearest neighbor Input: Query article: Xq Corpus of documents (N docs): (X1, X2, X3,... ,XN) output : XNN = min disance(Xq, Xi) 2. K-NN Algorit 阅读全文