├── Assignments.md ├── LICENSE ├── README.md ├── README_original_proposal.md ├── docs ├── README.md ├── export_model │ ├── group1-shard1of3.bin │ ├── group1-shard2of3.bin │ ├── group1-shard3of3.bin │ └── model.json ├── index.html └── index.js ├── lecture_01 ├── README.md ├── assignment01.md └── online_teacher.jpg ├── lecture_02 ├── 01_one_neuron_and_MPG_dataset.R ├── 01_one_neuron_and_MPG_dataset.ipynb ├── 02_dense_neural_network_and_MPG_dataset.R ├── 02_dense_neural_network_and_MPG_dataset.ipynb ├── 03_dense_neural_network_and_Titanic_dataset.R ├── 03_dense_neural_network_and_Titanic_dataset.ipynb ├── README.md └── titanic.csv ├── lecture_03 ├── README.md ├── mnist-fashion-keras-r.ipynb ├── mnist-fashion-keras.r ├── mnist_fashion_keras.ipynb └── mnist_fashion_keras.py ├── lecture_04 └── README.md ├── lecture_05 ├── Image_Downloader.ipynb ├── README.md └── Transfer_Learning_DogsAndCats.ipynb ├── lecture_06 ├── NLP_Zero_to_Hero_Combined_1_3.ipynb ├── README.md └── human_numbers │ ├── train.txt │ └── valid.txt ├── lecture_07 └── README.md ├── lecture_08 ├── README.md └── assignment │ ├── README.md │ ├── SimpleGenomicNN.ipynb │ ├── e_coli_promoters │ ├── e_coli_benchmark.ipynb │ ├── e_coli_benchmark_r.ipynb │ ├── e_coli_nonpromoters_train.fa │ ├── e_coli_nonpromoters_valid.fa │ ├── e_coli_promoters_train.fa │ └── e_coli_promoters_valid.fa │ └── g4 │ ├── G4_benchmark.ipynb │ ├── g4_notpresent_train.fa.gz │ ├── g4_notpresent_valid.fa.gz │ ├── g4_present_train.fa.gz │ └── g4_present_valid.fa.gz ├── lecture_09 ├── README.md ├── assignment │ ├── fake_v1_100x252.csv │ ├── pytips_v1_27x204.csv │ └── true_ratings.csv └── collaborative-filtering-r.ipynb ├── lecture_10 └── README.md ├── lecture_11 └── README.md └── lecture_12 └── README.md /Assignments.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/simecek/dspracticum2020/HEAD/Assignments.md 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