The Deep Learning Course
Meta-learning (one-shot or few-shot or zero-shot learning) OrTransfer learning (VGG16 or EfficientNetB0 or ResNet-50) OrDeep Neural Network (CNN or RNN or LSTM or GAN or any DNN)
Preferably perform the task https://github.com/sim0nsays/dlcourse_ai/blob/master/assignments/assignment6/RNNs.ipynb
But you can use any dataset with https://www.kaggle.com or any open-source dataset
The decision must be accompanied by the explanation of the steps taken, separately noting that it was done independently, unlike the source code - complete copying is unacceptable, will be a check on the plagiarism. Separately note that it should be highlighted in the report and in the presentation.In time - up to a week, the output requires a Collab file with the working code and the necessary explanations to the project.
Client's review of cooperation with Viktoriia M.
The Deep Learning CourseVery pleased with cooperation with Victoria, the project was done early, patiently answered stupid questions, in addition to the program part created a quality presentation, in a word, 5 out of 5, I can boldly recommend.
Freelancer's review of cooperation with Andrei Semenov
The Deep Learning CourseA good project with adequate communication and budget.
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A good project with normal communication and a proper budget.
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15892 378 0 1 Good day ,
I can do work according to the formulated requirements.
The budget is for a complex model.
The complexity of the model can be harmonised with any, but, as a rule, very complex models also cause questions when checking.
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