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Coursera Introduction to Machine Learning 2024

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Coursera - Introduction to Machine Learning 2024-3

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1.5 GB

Total Files

280

Last Seen

2025-08-31 00:14

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B46C7AAEB5FA99253AB6E5B6F0CD9EC5613CD2B1

/.../04_alternative-approaches/

01_simple-and-effective-alternative-methods-for-neural-nlp.mp4

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01_simple-and-effective-alternative-methods-for-neural-nlp.en.srt

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01_simple-and-effective-alternative-methods-for-neural-nlp.en.txt

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02_week-4-comprehensive_exam.html

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/.../01_logistic-regression/

01_course-information_instructions.html

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02_why-machine-learning-is-exciting.en.srt

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02_why-machine-learning-is-exciting.mp4

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02_why-machine-learning-is-exciting_1.1.10_Why_Machine_Learning_is_Exciting.pdf

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03_what-is-machine-learning.en.srt

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03_what-is-machine-learning_1.1.15_What_is_Machine_Learning.pdf

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04_intro-to-machine-learning_quiz.html

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05_logistic-regression.en.srt

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05_logistic-regression.mp4

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05_logistic-regression_1.1.20_Logistic_Regression.pdf

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06_interpretation-of-logistic-regression.en.srt

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06_interpretation-of-logistic-regression_1.1.30_Interpretatiof_Logistic_Regression.pdf

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07_math-for-data-science_instructions.html

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08_motivation-for-multilayer-perceptron.en.srt

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08_motivation-for-multilayer-perceptron_1.1.40_Motivation_for_Multilayer_Perceptron.pdf

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09_logistic-regression_quiz.html

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02_multilayer-perceptron-math-model_1.2.2_Multilayer_Perceptron_Math_Model.pdf

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03_multilayer-perceptron_quiz.html

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04_deep-learning_1.2.3_Deep_Learning.pdf

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05_example-document-analysis.en.srt

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06_interpretation-of-multilayer-perceptron.en.srt

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06_interpretation-of-multilayer-perceptron_1.2.5_Interpretation_of_Multilayer_Perceptron.pdf

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07_transfer-learning.en.srt

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07_transfer-learning_1.2.6_Transfer_Learning.pdf

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09_model-selection_1.2.7__Model_Selection.pdf

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10_model-selection_quiz.html

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11_early-history-of-neural-networks.en.srt

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11_early-history-of-neural-networks.mp4

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11_early-history-of-neural-networks_1.2.8_Early_History_of_Neural_Netorks.pdf

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12_history-of-neural-networks_quiz.html

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/.../03_convolutional-neural-networks/

01_hierarchical-structure-of-images.en.srt

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01_hierarchical-structure-of-images_1.3.1_Hierarchical_Structure_of_Images.pdf

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03_convolutional-neural-network.en.srt

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03_convolutional-neural-network_1.3.3_Convolutional_Neural_Network.pdf

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06_how-the-model-learns_1.3.5_How_the_Model_Learns.pdf

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07_advantages-of-hierarchical-features.en.srt

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07_advantages-of-hierarchical-features.mp4

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07_advantages-of-hierarchical-features_1.3.6_Advantages_of_Hierarchical_Features.pdf

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08_cnn-math-model_quiz.html

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/.../04_applications-in-the-real-world/

01_cnn-on-real-images.en.srt

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01_cnn-on-real-images.mp4

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01_cnn-on-real-images_1.4.1_CNN_on_Real_Images.pdf

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02_applications-in-use-and-practice.en.srt

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02_applications-in-use-and-practice_1.4.2_Applicatrions_in_use_and_practice.pdf

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03_deep-learning-and-transfer-learning.en.srt

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03_deep-learning-and-transfer-learning.mp4

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03_deep-learning-and-transfer-learning_1.4.3_Deep_Learning_and_Transfer_Learning.pdf

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04_applications-in-use-and-practice_quiz.html

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05_week-1-comprehensive_exam.html

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/.../05_pytorch-basics/

01_introduction-to-pytorch.en.srt

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01_introduction-to-pytorch.en.txt

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01_introduction-to-pytorch.mp4

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/.../01_logistic-regression-as-running-example/

01_how-do-we-define-learning.en.srt

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01_how-do-we-define-learning.mp4

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01_how-do-we-define-learning_2.1.10_How_do_we_define_learning.pdf

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02_how-do-we-evaluate-our-networks.en.srt

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02_how-do-we-evaluate-our-networks.en.txt

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02_how-do-we-evaluate-our-networks.mp4

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02_how-do-we-evaluate-our-networks_2.1.20_How_do_we_evaluate_our_networkds.pdf

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03_lesson-one_quiz.html

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/.../02_learning-via-gradient-descent/

01_how-do-we-learn-our-network.en.srt

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01_how-do-we-learn-our-network.mp4

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01_how-do-we-learn-our-network_2.2.10_How_do_we_learn_our_network.pdf

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02_how-do-we-handle-big-data.en.srt

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02_how-do-we-handle-big-data.mp4

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02_how-do-we-handle-big-data_2.2.20_How_do_we_handle_big_data.pdf

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03_early-stopping.en.srt

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03_early-stopping.en.txt

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03_early-stopping.mp4

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03_early-stopping_2.2.30_Early_Stopping.pdf

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04_lesson-2_quiz.html

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01_week-2-comprehensive_exam.html

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02_model-learning-with-pytorch.en.srt

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02_model-learning-with-pytorch.en.txt

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02_model-learning-with-pytorch.mp4

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/.../01_convolutional-neural-network-basics/

01_motivation-diabetic-retinopathy.en.srt

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01_motivation-diabetic-retinopathy.en.txt

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01_motivation-diabetic-retinopathy.mp4

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01_motivation-diabetic-retinopathy_3.1.10_Motivation_Diabetic_Retinopathy.pdf

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02_breakdown-of-the-convolution-1d-and-2d.en.srt

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02_breakdown-of-the-convolution-1d-and-2d.en.txt

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02_breakdown-of-the-convolution-1d-and-2d.mp4

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02_breakdown-of-the-convolution-1d-and-2d_3.1.20_Breakdown_of_the_Convolution_1D_and_2D.pdf

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03_lesson-one_quiz.html

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/.../02_core-components-of-the-network/

01_core-components-of-the-convolutional-layer.en.srt

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01_core-components-of-the-convolutional-layer.en.txt

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01_core-components-of-the-convolutional-layer.mp4

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01_core-components-of-the-convolutional-layer_3.2.10_Core_Components_of_the_Convolutional_Layer.pdf

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02_activation-functions.en.srt

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02_activation-functions.en.txt

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02_activation-functions.mp4

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02_activation-functions_3.2.30_Activations_Functions.pdf

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03_pooling-and-fully-connected-layers.en.srt

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03_pooling-and-fully-connected-layers.mp4

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03_pooling-and-fully-connected-layers_3.2.40_Pooling_and_fully_contected_layers.pdf

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04_lesson-2_quiz.html

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01_training-the-network.en.srt

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01_training-the-network.mp4

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01_training-the-network_3.3.10_Training_the_Network.pdf

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02_transfer-learning-and-fine-tuning.en.srt

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02_transfer-learning-and-fine-tuning_3.3.20_Transfer_Learning_and_Fine-Tuning.pdf

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03_lesson-3_quiz.html

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/.../04_convolutional-neural-networks-with-pytorch/

01_week-3-comprehensive_exam.html

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02_cnn-with-pytorch.en.srt

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/.../01_word-embeddings/

01_introduction-to-the-concept-of-word-vectors.en.srt

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01_introduction-to-the-concept-of-word-vectors.mp4

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01_introduction-to-the-concept-of-word-vectors_4.1.1_Introduction_to_the_Concept_of_Word_Vectors.pdf

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02_words-to-vectors.en.srt

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02_words-to-vectors_4.1.2_Words_to_Vectors.pdf

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03_example-of-word-embeddings.en.srt

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04_lesson-1_quiz.html

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01_neural-model-of-text.en.srt

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01_neural-model-of-text.mp4

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01_neural-model-of-text_4.2.1_Neural_model_of_text.pdf

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02_the-softmax-function.en.srt

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03_methods-for-learning-model-parameters.en.srt

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04_more-details-on-how-to-learn-model-parameters.en.srt

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05_lesson-2_quiz.html

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/.../03_recurrent-neural-networks-and-long-short-term-memory/

01_the-recurrent-neural-network.en.srt

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01_the-recurrent-neural-network.mp4

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02_long-short-term-memory.en.srt

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02_long-short-term-memory.mp4

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03_long-short-term-memory-review.en.srt

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03_long-short-term-memory-review.mp4

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04_use-of-lstm-for-text-synthesis.en.srt

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05_lesson-3_quiz.html

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/.../05_natural-language-processing-with-pytorch/

01_natural-language-processing-with-pytorch.en.srt

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/.../01_inner-products/

01_word-vectors-and-their-interpretation.en.srt

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01_word-vectors-and-their-interpretation.mp4

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02_relationships-between-word-vectors.en.srt

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03_inner-products-between-word-vectors.en.srt

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04_intuition-into-meaning-of-inner-products-of-word-vectors.en.srt

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/.../02_attention-mechanism/

01_introduction-of-attention-mechanism.en.srt

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02_queries-keys-and-values-of-attention-network.en.srt

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02_queries-keys-and-values-of-attention-network.mp4

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03_self-attention-and-positional-encodings.en.srt

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03_self-attention-and-positional-encodings.mp4

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/.../03_sequence-to-sequence-encoder-and-decoder/

01_attention-based-sequence-encoder.en.srt

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01_attention-based-sequence-encoder.mp4

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02_coupling-the-sequence-encoder-and-decoder.en.srt

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02_coupling-the-sequence-encoder-and-decoder.en.txt

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02_coupling-the-sequence-encoder-and-decoder.mp4

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03_cross-attention-in-the-sequence-to-sequence-model.en.srt

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/.../04_the-transformer-network/

01_multi-head-attention.en.srt

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01_multi-head-attention.mp4

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02_the-complete-transformer-network.en.srt

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/.../01_reinforcement-learning/

01_introduction-to-reinforcement-learning.en.srt

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01_introduction-to-reinforcement-learning.mp4

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02_reinforcement-learning-problem-setup.en.srt

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03_example-of-reinforcement-learning-in-practice.en.srt

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04_reinforcement-learning-quiz_quiz.html

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05_reinforcement-learning-with-pytorch.en.srt

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/02_q-learning/

01_moving-to-a-non-myopic-policy.en.srt

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01_moving-to-a-non-myopic-policy.mp4

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02_q-learning.en.srt

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02_q-learning.en.txt

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02_q-learning.mp4

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03_extensions-of-q-learning.en.srt

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03_extensions-of-q-learning.en.txt

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03_extensions-of-q-learning.mp4

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04_q-learning-quiz_quiz.html

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/.../03_deep-q-learning/

01_limitations-of-q-learning-and-introduction-to-deep-q-learning.en.srt

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01_limitations-of-q-learning-and-introduction-to-deep-q-learning.en.txt

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01_limitations-of-q-learning-and-introduction-to-deep-q-learning.mp4

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02_deep-q-learning-based-on-images.en.srt

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02_deep-q-learning-based-on-images.en.txt

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02_deep-q-learning-based-on-images.mp4

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03_connecting-deep-q-learning-with-conventional-q-learning.en.srt

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03_connecting-deep-q-learning-with-conventional-q-learning.en.txt

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03_connecting-deep-q-learning-with-conventional-q-learning.mp4

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04_deep-q-learning-quiz_quiz.html

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Total files 280


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