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DeepLearning AI TensorFlow Developer Professional Certificate
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[TutsNode.com] - DeepLearning.AI TensorFlow Developer Professional Certificate (Size: 1.21 GB) (Files: 598)
[TutsNode.com] - DeepLearning.AI TensorFlow Developer Professional Certificate
Convolutional Neural Networks in TensorFlow
04_multiclass-classifications
01_multiclass-classifications
03_introducing-the-rock-paper-scissors-dataset_rps.zip
02_moving-from-binary-to-multi-class-classification.en.srt
05_check-out-the-code_Course_2_-_Part_8_-_Lesson_2_-_Notebook_RockPaperS
03_introducing-the-rock-paper-scissors-dataset_instructions.html
05_check-out-the-code_instructions.html
07_try-testing-the-classifier_instructions.html
03_introducing-the-rock-paper-scissors-dataset_rps-test-set.zip
09_what-have-we-seen-so-far_instructions.html
01_a-conversation-with-andrew-ng.en.srt
08_test-the-rock-paper-scissors-classifier.en.srt
04_explore-multi-class-with-rock-paper-scissors-dataset.en.srt
06_train-a-classifier-with-rock-paper-scissors.en.srt
01_a-conversation-with-andrew-ng.mp4
03_introducing-the-rock-paper-scissors-dataset_rps-validation.zip
07_try-testing-the-classifier_rps-validation.zip
08_test-the-rock-paper-scissors-classifier.mp4
06_train-a-classifier-with-rock-paper-scissors.mp4
04_explore-multi-class-with-rock-paper-scissors-dataset.mp4
02_moving-from-binary-to-multi-class-classification.mp4
02_course-2-wrap-up
01_wrap-up_instructions.html
02_a-conversation-with-andrew-ng.en.srt
02_a-conversation-with-andrew-ng.mp4
01_exploring-a-larger-dataset
01_introduction
02_before-you-begin-tensorflow-2-0-and-this-course_instructions.html
01_introduction-a-conversation-with-andrew-ng.en.srt
01_introduction-a-conversation-with-andrew-ng.mp4
02_larger-dataset
01_a-conversation-with-andrew-ng.en.srt
02_the-cats-vs-dogs-dataset_instructions.html
04_looking-at-the-notebook_instructions.html
06_what-you-ll-see-next_instructions.html
07_fixing-through-cropping.en.srt
08_visualizing-the-effect-of-the-convolutions.en.srt
09_looking-at-accuracy-and-loss.en.srt
10_what-have-we-seen-so-far_instructions.html
11_week-1-wrap-up.en.srt
05_working-through-the-notebook.en.srt
06_what-you-ll-see-next_Course_2_-_Part_2_-_Lesson_2_-_Notebook.ipynb
04_looking-at-the-notebook_Course_2_-_Part_2_-_Lesson_2_-_Notebook.ipynb
03_training-with-the-cats-vs-dogs-dataset.en.srt
05_working-through-the-notebook.mp4
01_a-conversation-with-andrew-ng.mp4
08_visualizing-the-effect-of-the-convolutions.mp4
03_training-with-the-cats-vs-dogs-dataset.mp4
09_looking-at-accuracy-and-loss.mp4
11_week-1-wrap-up.mp4
07_fixing-through-cropping.mp4
02_augmentation-a-technique-to-avoid-overfitting
01_augmentation
02_image-augmentation_instructions.html
03_introducing-augmentation.en.srt
04_start-coding_instructions.html
06_looking-at-the-notebook_Course_2_-_Part_4_-_Lesson_2_-_Notebook_
06_looking-at-the-notebook_instructions.html
07_demonstrating-overfitting-in-cats-vs-dogs.en.srt
08_the-impact-of-augmentation-on-cats-vs-dogs_instructions.html
09_adding-augmentation-to-cats-vs-dogs.en.srt
10_try-it-for-yourself_instructions.html
12_what-have-we-seen-so-far_instructions.html
13_week-2-wrap-up.en.srt
10_try-it-for-yourself_Course_2_-_Part_4_-_Lesson_4_-_Notebook.ipyn
05_coding-augmentation-with-imagedatagenerator.en.srt
01_a-conversation-with-andrew-ng.en.srt
11_exploring-augmentation-with-horses-vs-humans.en.srt
01_a-conversation-with-andrew-ng.mp4
03_introducing-augmentation.mp4
05_coding-augmentation-with-imagedatagenerator.mp4
11_exploring-augmentation-with-horses-vs-humans.mp4
09_adding-augmentation-to-cats-vs-dogs.mp4
07_demonstrating-overfitting-in-cats-vs-dogs.mp4
13_week-2-wrap-up.mp4
03_transfer-learning
01_transfer-learning
03_start-coding_instructions.html
04_coding-transfer-learning-from-the-inception-mode.en.srt
05_adding-your-dnn_instructions.html
07_using-dropouts_instructions.html
08_exploring-dropouts.en.srt
09_applying-transfer-learning-to-cats-v-dogs_instructions.html
11_what-have-we-seen-so-far_instructions.html
12_week-3-wrap-up.en.srt
01_a-conversation-with-andrew-ng.en.srt
09_applying-transfer-learning-to-cats-v-dogs_Course_2_-_Part_6_-_Lesson_3_-_Notebook.ipynb
03_start-coding_Course_2_-_Part_6_-_Lesson_3_-_Notebook.ipynb
02_understanding-transfer-learning-the-concepts.en.srt
10_exploring-transfer-learning-with-inception.en.srt
06_coding-your-own-model-with-transferred-features.en.srt
01_a-conversation-with-andrew-ng.mp4
02_understanding-transfer-learning-the-concepts.mp4
10_exploring-transfer-learning-with-inception.mp4
12_week-3-wrap-up.mp4
08_exploring-dropouts.mp4
06_coding-your-own-model-with-transferred-features.mp4
04_coding-transfer-learning-from-the-inception-mode.mp4
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
02_introduction-to-computer-vision
02_weekly-exercise-implement-a-deep-neural-networ
01_introduction-to-computer-vision
09_get-hands-o
03_exploring-h
05_the-structu
11_see-how-to-
07_see-how-its
12_walk-throug
13_week-2-quiz
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01_a-conversat
06_coding-a-co
04_writing-cod
02_an-introduc
10_using-callb
01_a-new-programming-paradigm
02_weekly-exercise-your-first-neural-network
03_week-1
01_introd
02_exerci
01_a-new-programming-paradigm
04_the-hello-world-of-ne
07_try-it-for-yourself_i
01_before-you-begin-tens
05_from-rules-to-data_in
07_try-it-for-yourself_C
03_a-primer-in-machine-l
08_week-1-quiz_exam.html
06_working-through-hello
02_introduction-a-conver
04_using-real-world-images
02_weekly-exercise-handling-complex-images
02_week-4-reso
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01_using-real-world-images
03_understanding-imagegenerato
16_get-hands-on-with-compacted
14_get-hands-on-and-use-valida
13_adding-automatic-validation
12_experiment-with-the-horse-o
17_week-4-quiz_exam.html
02_explore-an-impactful-real-w
11_walking-through-training-th
04_designing-the-neural-networ
06_train-the-convnet-with-imag
01_a-conversation-with-andrew-
08_exploring-the-solution_inst
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05_defining-a-convnet-to-use-c
15_exploring-the-impact-of-com
07_training-the-convnet-with-f
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03_course-1-wrap-up
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02_a-conversation-with-andrew.en.srt
02_a-conversation-with-andrew.mp4
03_enhancing-vision-with-convolutional-neural-networks
02_weekly-exercise-improving-
01_enhancing-vision-with-conv
Natural Language Processing in TensorFlow
02_word-embeddings
01_word-embeddings
09_notebook-for-lesson-1.en.srt
09_notebook-for-lesson-1.mp4
13_check-out-the-code_Course_3_-_Week_2_-_Lesson_2.ipynb
08_check-out-the-code_Course_3_-_Week_2_-_Lesson_1.ipynb
19_check-out-the-code_Course_3_-_Week_2_-_Lesson_3.ipynb
20_notebook-for-lesson-3.en.srt
05_looking-into-the-details.en.srt
07_more-into-the-details.en.srt
01_a-conversation-with-andrew-ng.en.srt
06_how-can-we-use-vectors.en.srt
18_diving-into-the-code-part-2.en.srt
02_introduction.en.srt
11_building-a-classifier-for-the-sarcasm-dataset.en.srt
03_the-imbd-dataset.en.srt
04_imdb-reviews-dataset_instructions.html
08_check-out-the-code_instructions.html
10_remember-the-sarcasm-dataset.en.srt
12_lets-talk-about-the-loss-function.en.srt
13_check-out-the-code_instructions.html
14_pre-tokenized-datasets.en.srt
16_diving-into-the-code-part-1.en.srt
15_tensorflow-datasets_instructions.html
17_subwords-text-encoder_instructions.html
19_check-out-the-code_instructions.html
21_week-2-wrap-up_instructions.html
01_a-conversation-with-andrew-ng.mp4
02_introduction.mp4
06_how-can-we-use-vectors.mp4
20_notebook-for-lesson-3.mp4
18_diving-into-the-code-part-2.mp4
12_lets-talk-about-the-loss-function.mp4
05_looking-into-the-details.mp4
07_more-into-the-details.mp4
14_pre-tokenized-datasets.mp4
03_the-imbd-dataset.mp4
10_remember-the-sarcasm-dataset.mp4
11_building-a-classifier-for-the-sarcasm-dataset.mp4
16_diving-into-the-code-part-1.mp4
01_sentiment-in-text
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12_working-with-the-tokenizer.en.srt
16_week-1-wrap-up.en.srt
04_check-out-the-code_Course_3_-_Week_1_-_Lesson_1.ipynb
09_check-out-the-code_Course_3_-_Week_1_-_Lesson_2.ipynb
14_check-out-the-code_Course_3_-_Week_1_-_Lesson_3.ipynb
10_notebook-for-lesson-2.en.srt
13_news-headlines-dataset-for-sarcasm-detection_instructions.html
06_text-to-sequence.en.srt
11_sarcasm-really.en.srt
05_notebook-for-lesson-1.en.srt
15_notebook-for-lesson-3.en.srt
03_using-apis.en.srt
01_introduction.en.srt
04_check-out-the-code_instructions.html
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09_check-out-the-code_instructions.html
08_padding.en.srt
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07_looking-more-at-the-tokenizer.en.srt
10_notebook-for-lesson-2.mp4
15_notebook-for-lesson-3.mp4
06_text-to-sequence.mp4
07_looking-more-at-the-tokenizer.mp4
01_introduction.mp4
11_sarcasm-really.mp4
08_padding.mp4
03_using-apis.mp4
02_word-based-encodings.mp4
05_notebook-for-lesson-1.mp4
12_working-with-the-tokenizer.mp4
16_week-1-wrap-up.mp4
01_introduction
01_introduction-a-conversation-with-andrew-ng.en.srt
01_introduction-a-conversation-with-andrew-ng.mp4
04_sequence-models-and-literature
01_sequence-models-and-literature
12_link-to-laurences-poetry_irish-lyrics-eof.txt
15_check-out-the-code_Course_3_-_Week_4_-_Lesson_2_-_Notebook.ipyn
06_check-out-the-code_Course_3_-_Week_4_-_Lesson_1_-_Notebook.ipyn
07_notebook-for-lesson-1.en.srt
04_training-the-data.en.srt
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01_a-conversation-with-andrew-ng.en.srt
02_introduction.en.srt
13_looking-into-the-code.en.srt
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14_laurence-the-poet.en.srt
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03_looking-into-the-code.en.srt
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12_link-to-laurences-poetry_instructions.html
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07_notebook-for-lesson-1.mp4
01_a-conversation-with-andrew-ng.mp4
02_introduction.mp4
08_finding-what-the-next-word-should-be.mp4
14_laurence-the-poet.mp4
16_your-next-task.mp4
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10_predicting-a-word.mp4
11_poetry.mp4
13_looking-into-the-code.mp4
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01_wrap-up_instructions.html
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03_sequence-models
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12_check-out-the-code_Course_3_-_Week_3_-_Lesson_1c.ipynb
14_check-out-the-code_Course_3_-_Week_3_-_Lesson_2d.ipynb
16_exploring-different-sequence-models_Course_3_-_Week_3_-_Lesson_2.ipynb
16_exploring-different-sequence-models_Course_3_-_Week_3_-_Lesson_2c.ipynb
05_more-info-on-lstms_instructions.html
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13_going-back-to-the-imdb-dataset.en.srt
16_exploring-different-sequence-models_instructions.html
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09_a-word-from-laurence.en.srt
14_check-out-the-code_instructions.html
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15_tips-from-laurence.en.srt
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04_lstms.mp4
10_looking-into-the-code.mp4
11_using-a-convolutional-network.mp4
13_going-back-to-the-imdb-dataset.mp4
06_implementing-lstms-in-code.mp4
Sequences, Time Series and Prediction
01_sequences-and-prediction
02_sequences-and-prediction
11_forecasting-notebook_SP_Week_1_-_Lesson_3_-_Notebook.ipynb
03_common-patterns-in-time-series.en.srt
05_introduction-to-time-series-notebook_instructions.html
05_introduction-to-time-series-notebook_SP_Week_1_Lesson_2.ipynb
10_forecasting.en.srt
01_time-series-examples.en.srt
04_introduction-to-time-series.en.srt
02_machine-learning-applied-to-time-series.en.srt
06_train-validation-and-test-sets.en.srt
08_moving-average-and-differencing.en.srt
07_metrics-for-evaluating-performance.en.srt
09_trailing-versus-centered-windows.en.srt
12_week-1-wrap-up_instructions.html
11_forecasting-notebook_instructions.html
10_forecasting.mp4
04_introduction-to-time-series.mp4
01_time-series-examples.mp4
03_common-patterns-in-time-series.mp4
06_train-validation-and-test-sets.mp4
08_moving-average-and-differencing.mp4
02_machine-learning-applied-to-time-series.mp4
07_metrics-for-evaluating-performance.mp4
09_trailing-versus-centered-windows.mp4
01_introduction
01_introduction-a-conversation-with-andrew-ng.en.srt
01_introduction-a-conversation-with-andrew-ng.mp4
03_recurrent-neural-networks-for-time-series
01_recurrent-neural-networks-for-time-series
14_lstm-notebook_SP_Week_3_Lesson_4_-_LSTM.ipynb
09_rnn-notebook_SP_Week_3_Lesson_2_-_RNN.ipynb
01_week-3-a-conversation-with-andrew-ng.mp4
02_conceptual-overview.en.srt
01_week-3-a-conversation-with-andrew-ng.en.srt
06_adjusting-the-learning-rate-dynamically.en.sr
12_coding-lstms.en.srt
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10_lstm.en.srt
13_more-on-lstm.en.srt
08_rnn.en.srt
04_outputting-a-sequence.en.srt
14_lstm-notebook_instructions.html
15_week-3-wrap-up_instructions.html
09_rnn-notebook_instructions.html
11_link-to-the-lstm-lesson_instructions.html
07_more-info-on-huber-loss_instructions.html
02_conceptual-overview.mp4
13_more-on-lstm.mp4
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10_lstm.mp4
03_shape-of-the-inputs-to-the-rnn.mp4
05_lambda-layers.mp4
04_outputting-a-sequence.mp4
02_deep-neural-networks-for-time-series
01_deep-neural-networks-for-time-series
11_single-layer-neural-network-notebook_SP_Week_2_Lesson_2
04_preparing-features-and-labels-notebook_SP_Week_2_Lesson
14_deep-neural-network-notebook_SP_Week_2_Lesson_3.ipynb
12_deep-neural-network-training-tuning-and-prediction.en.s
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01_a-conversation-with-andrew-ng.en.srt
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15_week-2-wrap-up_instructions.html
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11_single-layer-neural-network-notebook_instructions.html
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12_deep-neural-network-training-tuning-and-prediction.mp4
13_deep-neural-network.mp4
03_preparing-features-and-labels.mp4
01_a-conversation-with-andrew-ng.mp4
02_preparing-features-and-labels.mp4
10_more-on-single-layer-neural-network.mp4
09_prediction.mp4
07_single-layer-neural-network.mp4
06_feeding-windowed-dataset-into-neural-network.mp4
08_machine-learning-on-time-windows.mp4
04_real-world-time-series-data
01_real-world-time-series-data
07_lstm-notebook_SP_Week_4_Lesson_1.ipynb
12_sunspots-notebook_SP_Week_4_Lesson_3.ipynb
12_sunspots-notebook_SP_Week_4_Lesson_5.ipynb
13_combining-our-tools-for-analysis.en.srt
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13_combining-our-tools-for-analysis.mp4
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10_prediction.mp4
09_train-and-tune-the-model.mp4
02_convolutions.mp4
03_tensorflow-in-practice-has-come-to-an-end
01_specialization-wrap-up-a-conversation-with-andrew-ng.en.srt
02_what-next_instructions.html
01_specialization-wrap-up-a-conversation-with-andrew-ng.mp4
02_course-4-wrap-up
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01_wrap-up_instructions.html
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