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*Total -- 53,858.05kb -> 43,285.75kb (19.63%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/images/outliers_padding_ex.png -- 25.24kb -> 9.11kb (63.89%) /Chapter-wise code/Code - PyTorch/2. Convolution Neural Networks/8. Autoencoders/images/learning_autoencoder.png -- 12.69kb -> 5.56kb (56.16%) /Chapter-wise code/Code - PyTorch/2. Convolution Neural Networks/8. Autoencoders/images/sparse_encoders.png -- 7.91kb -> 3.48kb (55.94%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/13. Siamese Networks/Question Duplication/images/quora_dataset.png -- 75.64kb -> 33.74kb (55.39%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/gradient_of_loss.png -- 7.08kb -> 3.45kb (51.3%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/en_fr_train.png -- 5.31kb -> 2.61kb (50.82%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/final_loss_function.png -- 5.47kb -> 2.73kb (50.14%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/fr_embedding.png -- 6.92kb -> 3.47kb (49.91%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/13. Siamese Networks/Question Duplication/images/new_triplet_loss.png -- 39.07kb -> 19.63kb (49.76%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/en_embeddings.png -- 7.65kb -> 3.87kb (49.39%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/accuracy.png -- 6.24kb -> 3.16kb (49.39%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/cosine_similarity.png -- 3.62kb -> 1.84kb (49.18%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/translation_problem.png -- 3.60kb -> 1.95kb (45.91%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/modified_forbenius_norm.png -- 3.02kb -> 1.66kb (44.96%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/description.png -- 5.85kb -> 3.25kb (44.49%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/1. Text generation using RNNs/assets/charRNN.png -- 32.69kb -> 18.47kb (43.48%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/update_r.png -- 3.03kb -> 1.73kb (42.84%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/distance_formula.png -- 3.22kb -> 1.87kb (42.08%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/1. Generating hand-written digits using GANs/images/tanh_fn.png -- 216.79kb -> 126.69kb (41.56%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/1. Text generation using RNNs/assets/sequence_batching@1x.png -- 55.89kb -> 32.68kb (41.53%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/13. Siamese Networks/Question Duplication/images/triplet_loss.png -- 14.70kb -> 8.63kb (41.26%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/1. Generating hand-written digits using GANs/images/leaky_relu.png -- 239.64kb -> 142.08kb (40.71%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/6. Machine Translation/NMT-Basic/images/original_forbenius_norm.png -- 2.40kb -> 1.45kb (39.55%) /Chapter-wise notes/Ch_1_Linear_algebra/images/eigen_decompost.png -- 4.23kb -> 2.63kb (37.8%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/images/CycleGAN_loss.png -- 139.58kb -> 87.27kb (37.48%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/3. Cyclic GANs/Image-to-Image Translation via Cyclic GANs/images/CycleGAN_loss.png -- 139.58kb -> 87.27kb (37.48%) /Chapter-wise code/Code - PyTorch/2. Convolution Neural Networks/8. Autoencoders/images/denoising.png -- 34.70kb -> 21.73kb (37.36%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/3. Cyclic GANs/Image-to-Image Translation via Cyclic GANs/images/cyclegan_generator_ex.png -- 151.93kb -> 95.25kb (37.31%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/images/cyclegan_generator_ex.png -- 151.93kb -> 95.25kb (37.31%) /Chapter-wise code/Code - PyTorch/2. Convolution Neural Networks/8. Autoencoders/images/DAE.png -- 1.46kb -> 0.92kb (37.22%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/3. Cyclic GANs/Image-to-Image Translation via Cyclic GANs/images/discriminator_layers.png -- 104.30kb -> 65.72kb (36.99%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/images/discriminator_layers.png -- 104.30kb -> 65.72kb (36.99%) /Chapter-wise notes/Ch_8_Convolutional_Neural_Networks/images/30.eca_1.png -- 5.92kb -> 3.75kb (36.71%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/images/network_diagram.png -- 25.88kb -> 16.38kb (36.7%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/1. Text generation using RNNs/assets/sequence_batching_ex.png -- 124.59kb -> 79.80kb (35.95%) /Chapter-wise notes/Ch_1_Linear_algebra/images/frob_in_trace.png -- 4.11kb -> 2.69kb (34.69%) /Chapter-wise notes/Ch_1_Linear_algebra/images/norms.png -- 4.17kb -> 2.73kb (34.61%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/1. Generating hand-written digits using GANs/images/gan_network.png -- 22.58kb -> 14.80kb (34.47%) /Chapter-wise notes/Ch_1_Linear_algebra/images/max_norm.png -- 3.45kb -> 2.27kb (34.25%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/12. Dot product.png -- 488.90kb -> 321.92kb (34.15%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/1. Text generation using RNNs/assets/sequence_batching.png -- 23.58kb -> 15.60kb (33.85%) /Chapter-wise notes/Ch_2_Probability_and_Information_Theorey/images/43.self_information.png -- 3.63kb -> 2.41kb (33.81%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/11. Autocorrect Tool/images/auto-correct.png -- 118.32kb -> 79.16kb (33.09%) /Chapter-wise notes/Ch_1_Linear_algebra/images/l1_norm.png -- 3.04kb -> 2.09kb (31.09%) /Chapter-wise code/Code - PyTorch/2. Convolution Neural Networks/8. Autoencoders/images/conv_enc_2.png -- 207.53kb -> 143.84kb (30.69%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/15. step - 1.png -- 125.48kb -> 87.18kb (30.52%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/6. topic matrix -2.png -- 306.85kb -> 213.49kb (30.42%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/16. sample a topic - 1.png -- 374.49kb -> 261.79kb (30.09%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/7. topic matrix - 1.png -- 298.55kb -> 208.83kb (30.05%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/14. Sample a topic-3.png -- 497.99kb -> 348.83kb (29.95%) /Chapter-wise notes/Ch_1_Linear_algebra/images/trace_transpose.png -- 3.52kb -> 2.47kb (29.92%) /Chapter-wise notes/Ch_6_Regularization_for_Deep_Learning/images/51.bagging_3.png -- 3.08kb -> 2.16kb (29.82%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/9. Skip-gram model.png -- 746.83kb -> 524.35kb (29.79%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/3. Matrix multiplication .png -- 624.24kb -> 441.60kb (29.26%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/8. Beta Distribution .png -- 252.73kb -> 178.82kb (29.25%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/10. decimal beta distribution .png -- 313.58kb -> 222.46kb (29.06%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/15. sample a topic - 2.png -- 655.19kb -> 464.83kb (29.05%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/3. matrix.png -- 465.81kb -> 330.79kb (28.99%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/3. document-term matric.png -- 465.81kb -> 330.79kb (28.99%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/1. C-BOW.png -- 402.19kb -> 285.91kb (28.91%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/13. Siamese Networks/Question Duplication/images/siamese_networks.png -- 267.54kb -> 190.57kb (28.77%) /Chapter-wise code/Code - PyTorch/7. Attention Models/1. NMT/images/8. NMT with attention.png -- 253.07kb -> 180.34kb (28.74%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/13. Siamese Networks/Question Duplication/images/sample_output_2.png -- 69.64kb -> 49.66kb (28.69%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/2. text cleaning.png -- 295.47kb -> 210.91kb (28.62%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/4. Matrix multiplcation max.png -- 677.38kb -> 483.74kb (28.59%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/12. Dirichlet distribution .png -- 431.57kb -> 308.23kb (28.58%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/6. TF-IDF Matrix.png -- 482.89kb -> 345.33kb (28.49%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/5. BOW-Matrix.png -- 408.77kb -> 292.60kb (28.42%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/20. final topic model.png -- 621.05kb -> 444.78kb (28.38%) /Chapter-wise notes/Ch_8_Convolutional_Neural_Networks/images/14.equivariance.png -- 14.23kb -> 10.21kb (28.25%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/1. BOW.png -- 166.51kb -> 119.74kb (28.09%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/18. sample a word - 3.png -- 459.65kb -> 332.78kb (27.6%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/19. combining models.png -- 593.49kb -> 429.75kb (27.59%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/16. sample a word-1.png -- 370.33kb -> 268.45kb (27.51%) /Chapter-wise code/Code - PyTorch/2. Convolution Neural Networks/8. Autoencoders/images/autoencoder_denoise.png -- 135.98kb -> 98.78kb (27.36%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/17. sample a word -2.png -- 520.15kb -> 378.19kb (27.29%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/6. document matrix.png -- 243.23kb -> 176.93kb (27.26%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/images/reviews_ex.png -- 66.56kb -> 48.47kb (27.19%) /Chapter-wise code/Code - PyTorch/2. Convolution Neural Networks/8. Autoencoders/images/conv_enc_1.png -- 151.92kb -> 110.76kb (27.1%) /Chapter-wise code/Code - PyTorch/3. Recurrent Neural Networks/1. Text generation using RNNs/assets/charRNN@0.5x.png -- 15.81kb -> 11.55kb (26.94%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/2. Latent Variables.png -- 355.89kb -> 260.58kb (26.78%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/2. basic encoder-decoder.png -- 311.37kb -> 228.01kb (26.77%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/11. step - 5.png -- 166.55kb -> 122.01kb (26.74%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/7. One-Hot Encoding.png -- 297.62kb -> 218.06kb (26.73%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/4. Corpus & Vocab.png -- 296.62kb -> 217.34kb (26.73%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/13. Siamese Networks/Question Duplication/images/sample_output_1.png -- 62.00kb -> 45.53kb (26.56%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/1. Naive Bayes Classifier/images/NLP Pipeline.png -- 423.16kb -> 310.97kb (26.51%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/19. Topic model.png -- 870.01kb -> 639.92kb (26.45%) /Chapter-wise notes/Ch_5_Deep_Forward_Networks/Ch_5.1_Back_Propagation/images/back_prop_2.png -- 26.67kb -> 19.64kb (26.37%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/images/training_cycle_ex.png -- 184.52kb -> 136.44kb (26.06%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/3. Cyclic GANs/Image-to-Image Translation via Cyclic GANs/images/training_cycle_ex.png -- 184.52kb -> 136.44kb (26.06%) /Chapter-wise notes/Ch_5_Deep_Forward_Networks/Ch_5.1_Back_Propagation/images/forward_pass.png -- 23.42kb -> 17.36kb (25.87%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/9. step - 3.png -- 251.84kb -> 186.80kb (25.83%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/1. drawbacks of seq2seq.png -- 241.22kb -> 179.17kb (25.73%) /Chapter-wise notes/Ch_1_Linear_algebra/images/SVD.png -- 2.62kb -> 1.95kb (25.62%) /Chapter-wise notes/Ch_5_Deep_Forward_Networks/Ch_5.1_Back_Propagation/images/07.b_computation.png -- 43.40kb -> 32.34kb (25.49%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/3. transformer model.png -- 301.77kb -> 224.86kb (25.49%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/10. step - 4.png -- 280.26kb -> 208.86kb (25.48%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/8. step - 2.png -- 224.99kb -> 167.68kb (25.47%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/12. step - 6.png -- 197.75kb -> 147.80kb (25.26%) /Chapter-wise notes/Ch_5_Deep_Forward_Networks/Ch_5.1_Back_Propagation/images/06.f_computation.png -- 31.97kb -> 23.90kb (25.26%) /Chapter-wise notes/Ch_4_Machine_Learning_Basics/images/38. variance.png -- 8.29kb -> 6.20kb (25.22%) /Chapter-wise notes/Ch_5_Deep_Forward_Networks/Ch_5.1_Back_Propagation/images/back_prop_final_algo.png -- 65.62kb -> 49.11kb (25.15%) /Chapter-wise notes/Ch_1_Linear_algebra/images/orthonormal_matrix.png -- 2.91kb -> 2.18kb (25.07%) /Chapter-wise notes/Ch_5_Deep_Forward_Networks/Ch_5.1_Back_Propagation/images/back_prop_3.png -- 65.62kb -> 49.25kb (24.94%) /Chapter-wise notes/Ch_2_Probability_and_Information_Theorey/images/41.Properties_of_softplus.png -- 23.15kb -> 17.38kb (24.93%) /Chapter-wise notes/Ch_8_Convolutional_Neural_Networks/images/08.toeplitz_matrix_1d.png -- 12.13kb -> 9.11kb (24.85%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/4. Topic Modelling/images/13. 3D D Distributions.png -- 664.15kb -> 500.93kb (24.58%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/22. step - 1.png -- 337.22kb -> 254.78kb (24.45%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/8. Word Embeddings.png -- 245.76kb -> 185.69kb (24.44%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/14. step - 8.png -- 205.73kb -> 155.60kb (24.37%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/11. Co-occurance probability.png -- 438.21kb -> 331.56kb (24.34%) /Chapter-wise code/Code - PyTorch/5. Deploy Models to PROD via Amazon Sagemaker/2. Deploy your own sentiment analysis model/Img/pos_review.png -- 35.03kb -> 26.54kb (24.26%) /Chapter-wise code/Code - PyTorch/7. Attention Models/1. NMT/images/3. word alignment.png -- 214.96kb -> 163.13kb (24.11%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/9. Word Embeddings - 1.png -- 212.00kb -> 160.96kb (24.07%) /Chapter-wise notes/Ch_4_Machine_Learning_Basics/images/23. Bayesian_stats.png -- 5.47kb -> 4.16kb (23.94%) /Chapter-wise notes/Ch_6_Regularization_for_Deep_Learning/images/52.bagging_4.png -- 9.88kb -> 7.52kb (23.88%) /Chapter-wise code/Code - PyTorch/7. Attention Models/1. NMT/images/9. flexible attention.png -- 207.10kb -> 157.83kb (23.79%) /Chapter-wise code/Code - PyTorch/7. Attention Models/1. NMT/images/6. Inside attention layer.png -- 284.08kb -> 216.50kb (23.79%) /Chapter-wise notes/Ch_1_Linear_algebra/images/normas_2.png -- 2.37kb -> 1.80kb (23.74%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/13. step - 7.png -- 189.13kb -> 144.68kb (23.5%) /Chapter-wise code/Code - PyTorch/7. Attention Models/2. Neural Text Summarization/images/7. step - 1.png -- 154.82kb -> 118.85kb (23.23%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/3. Feature Extraction & Embeddings/images/10. Word2Vec.png -- 338.60kb -> 260.85kb (22.96%) /Chapter-wise notes/Ch_5_Deep_Forward_Networks/images/50. SSE.png -- 4.09kb -> 3.15kb (22.96%) /Chapter-wise code/Code - PyTorch/5. Deploy Models to PROD via Amazon Sagemaker/2. Deploy your own sentiment analysis model/Img/neg_review.png -- 45.31kb -> 34.95kb (22.87%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/2. Parts of Speech Tagging/images/3. Bigrams.png -- 484.46kb -> 373.73kb (22.86%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/2. Parts of Speech Tagging/images/7. Transition Probability.png -- 608.32kb -> 469.48kb (22.82%) /Chapter-wise code/Code - PyTorch/7. Attention Models/1. NMT/images/1. basic seq-to-seq model.png -- 242.75kb -> 187.35kb (22.82%) /Chapter-wise notes/Ch_2_Probability_and_Information_Theorey/images/7. Conditional_prob.png -- 3.79kb -> 2.92kb (22.82%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/images/resnet_block.png -- 33.53kb -> 25.91kb (22.73%) /Chapter-wise code/Code - PyTorch/4. Generative Adversarial Networks (GANs)/3. Cyclic GANs/Image-to-Image Translation via Cyclic GANs/images/resnet_block.png -- 33.53kb -> 25.91kb (22.73%) /Chapter-wise code/Code - PyTorch/6. Natural-Language-Processing/2. Parts of Speech Tagging/images/2. look-up table.png -- 416.13kb -> 321.70kb (22.69%) /Chapter-wise code/Code - PyTorch/7. Attention Models/1. NMT/images/20. step - 6.png -- 306.69kb -> 237.71kb (22.49%) /Chapter-wise notes/Ch_4_Machine_Learning_Basics/images/23. 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