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Natural Language Processing with TensorFlow 2 - Beginner's Course

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Rating: 4.0; Vote: 1

This course is a practical introduction to natural language processing with TensorFlow 2.0. In this tutorial you will go from having zero knowledge to writing an artificial intelligence that can compose Shakespearean prose. No prior experience with deep learning is required, though it is always helpful to have more background information. We-ll use a combination of embedding layers, recurrent neural networks, and fully connected layers to perform the classification. --Course Contents -- -- (01:16) Getting Started with Word Embeddings -- (33:25) How to Perform Sentiment Analysis on Movie Reviews -- (59:32) Let-s Write An AI That Writes Shakespeare --Course Description -- The basic idea behind natural language processing is that we start out with words, i.e. strings of characters, that are almost impossible for the computer to meaningfully parse. We can transform these strings into a vector in a higher dimensional space. Different words will be represented as vectors of different lengths and directions in this space, and this allows us to find relationships between words by finding the component of one vector along another. Don-t worry, the TensorFlow library handles all of this, we just have to have some basic idea of how it works. Since this is a type of supervised learning, we also have labels for our text. This allows the AI to compare the relationships between words to the training labels, and learn which sequences of words represent good and bad movie reviews. This would also work for finding toxic comments, fake product reviews- just about anything for which we need a multiclass classification of text - provided we have enough training data and labels. The last step in complexity is to change the final layer that handles the classification. This allows us to actually output text that the AI thinks is meaningful. What-s really special about this is that the neural network starts out not even knowing that letters are a thing, or that we use spaces and punctuation, to producing something that approximates human level writing. --Code -- -Word Embeddings: https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/text/word_embeddings.ipynb -Text Classification: https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/text/text_classification_rnn.ipynb -Text Generation: https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/text/text_generation.ipynb --Resources -- As stated in the videos, these are from the official TensorFlow tutorials. You can find them here: -https://www.tensorflow.org/tutorials/text/word_embeddings -https://www.tensorflow.org/tutorials/text/text_classification_rnn -https://www.tensorflow.org/tutorials/text/text_generation This course was created by Phil Tabor. If you-d like to see more deep learning, reinforcement learning, and artificial intelligence content, please check out his channel: https://www.youtube.com/MachineLearningWithPhil
Date: 2022-03-14

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Comments and reviews: 10

Parakeet
That's a garbage tutorial. The code you're using is not generalizeable at all. When people inevitably deal with data that isn't from Tensorflow Datasets, how are they going to replace -encoder = info.features['text'].encoder-. I have no idea what it does: it's Tensorflow specific. You should have turned the Tensorflow dataset into a Numpy array or a list immediately.
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Muhammad
I am getting a ConnectionResetError in tfds.load method in the code shown at 10:30 in the video. I can't seem to find any help on stackoverflow or any other site. has anyone got this problem and figured it out? please help with this, thanks
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Ki
41:36 so cute lol
Went through this tutorial after finished Patrick Loeber's TF playlist. Imo Patrick's code is friendlier to read.
This is probably not a good tutorial for TF beginners, but a great one after you learn the basics of TF.
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Nikos
Hello, have you explored how to build a custom encoder decoder architecture with tf2? For example machine translation, but to be able to run with variable length sequences, not just pad to maximum overall length.
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Phillip
You're not really explaining what you're doing as you're going... Which is a shame. Appreciate there's a lot of documentation to refer to, but 'beginners course' is a bit of a misnomer
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Arjun
The Last Jedi was polarizing at best. Its got great critic reviews and poor audience reviews. But the SW audience is kinda infamous for their immaturity so
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EarlZMoade
For vim you should have a look at the coc.nvim plugin with the coc-python extension. It'll prevent you missing syntax errors before running the file.
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Wizartar
very good video to get an overview of this stuff, but aren't uncompiled languages just so much fun to work with! run.run.run.typo!
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Kenzie7
I got my first job as a software engineer thanks to freeCodeCamp. I cannot thank you guys enough. I will definitely donate soon
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Tuna
I think this requires some background, I do not know much about TF and in first 15 minutes, I did not understand what is going on.
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