4 Inception v2とInception v3の違いは何ですか? 紙の畳み込みで、より深い行くには、元の開始モジュールを含むGoogleNetについて説明します。 Inception v2の変更点は、5x5の畳み込みを2つの連続した3x3の畳み込みに置き換え、プーリングを適用したことです。 Inception v2とInception v3の違いは何ですか? 18 image-classification convnet computer-vision inception
5 シーボーンヒートマップを大きくする corr()元のdfからdf を作成します。corr()DFは、70 X 70から出てきたし、ヒートマップを可視化することは不可能です... sns.heatmap(df)。を表示しようとするcorr = df.corr()と、テーブルが画面に収まらず、すべての相関関係を確認できます。dfサイズに関係なく全体を印刷する方法ですか、ヒートマップのサイズを制御する方法ですか? 16 visualization pandas plotting machine-learning neural-network svm decision-trees svm efficiency python linear-regression machine-learning nlp topic-model lda named-entity-recognition naive-bayes-classifier association-rules fuzzy-logic kaggle deep-learning tensorflow inception classification feature-selection feature-engineering machine-learning scikit-learn tensorflow keras encoding nlp text-mining nlp rnn python neural-network feature-extraction machine-learning predictive-modeling python r linear-regression clustering r ggplot2 neural-network neural-network training python neural-network deep-learning rnn predictive-modeling databases sql programming distribution dataset cross-validation neural-network deep-learning rnn machine-learning machine-learning python deep-learning data-mining tensorflow visualization tools sql embeddings orange feature-extraction unsupervised-learning gan machine-learning python data-mining pandas machine-learning data-mining bigdata apache-spark apache-hadoop deep-learning python convnet keras aggregation clustering k-means r random-forest decision-trees reference-request visualization data pandas plotting neural-network keras rnn theano deep-learning tensorflow inception predictive-modeling deep-learning regression sentiment-analysis nlp encoding deep-learning python scikit-learn lda convnet keras predictive-modeling regression overfitting regression svm prediction machine-learning similarity word2vec information-retrieval word-embeddings neural-network deep-learning rnn
3 Tensorflowでバッチ内積を行う方法は? 2つのテンソルがありa:[batch_size, dim] b:[batch_size, dim]ます。バッチ内のすべてのペアに対して内積を行い、を生成c:[batch_size, 1]しc[i,0]=a[i,:].T*b[i,:]ます。どうやって? 10 tensorflow scikit-learn svm cross-validation feature-selection bayesian machine-learning decision-trees parameter-estimation neural-network convnet neural-network regularization visualization machine-learning similarity python pandas indexing r data-cleaning machine-learning predictive-modeling data-cleaning recommender-system python sequential-pattern-mining software-recommendation r visualization gaussian distribution machine-learning data-mining bigdata apache-hadoop predictive-modeling logistic-regression sampling machine-learning regression feature-selection mongodb neural-network inception machine-learning classification dataset databases logistic-regression deep-learning backpropagation classification data-mining multilabel-classification text-mining data-cleaning unsupervised-learning anomaly-detection python r python pandas