Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial

This course will give you an introduction to machine learning concepts and neural network implementation using Python and TensorFlow. Kylie Ying explains basic concepts, such as classification, regression, training/validation/test datasets, loss functions, neural networks, and model training. She then demonstrates how to implement a feedforward neural network to predict whether someone has diabetes, as well as two different neural net architectures to classify wine reviews.

✏️ Course created by Kylie Ying.

This course was made possible by a grant from Google's TensorFlow team.

⭐️ Resources ⭐️

⭐️ Course Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:00:34) Colab intro (importing wine dataset)
⌨️ (0:07:48) What is machine learning?
⌨️ (0:14:00) Features (inputs)
⌨️ (0:20:22) Outputs (predictions)
⌨️ (0:25:05) Anatomy of a dataset
⌨️ (0:30:22) Assessing performance
⌨️ (0:35:01) Neural nets
⌨️ (0:48:50) Tensorflow
⌨️ (0:50:45) Colab (feedforward network using diabetes dataset)
⌨️ (1:21:15) Recurrent neural networks
⌨️ (1:26:20) Colab (text classification networks using wine dataset)
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🎉 Thanks to our Champion and Sponsor supporters:
👾 Raymond Odero
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👾 Otis Morgan
👾 DeezMaster

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[KylieYYing]

Thanks for watching everyone! I hope you enjoy learning from the examples in this course :)

[francis.joseph]

great content.
explained in layman terms without wasting time 👌🏻

[ytwt]

[04:39] Just to be clear, `NaN` is not a "none-type value" indicating that "no value [was] recorded [there]" —that'd be `undefined`. It stands for "not a number" and is the result returned from trying to do an operation that can only be done on an Int/Float (or something that will be coerced into an Int/Float) on a value that isn't an Int/Float; e.g., `4 * "dog"` in JS will return `NaN`. It means you tried to do something with a number that's irrational to do with an number. Another JS example: zero divided by zero.

[businessTech]

you way of explaining is so good this was the first video i watched on Neural networks and iam already in love with it.

[vinniepathe]

It is really good. I am halfway through and it keeps you engaged and learning at the same time. Great job Kylie.

[stevemulcahy]

This was a great video. My only questions from it would be:
1) How would you set these projects up outside of colab?
2) How do we utilize the model?

[MAKARANDMALI]

Excellent tutorial, There are two questions. 1. Can I use open-source large language models in your text classification code for analyzing a wine review dataset?. 2. If yes plz suggest me where and how i can change.

[ArdhiSasongko-hp]

not hot dog :D, this part is still round in my mind, and the funny part for helping me to grasp what is binary classification is

[suomynona]

Thank you for making this! Please make it a series if you can

[KumR]

Hi Kylie.... Big fan of your work... Quick Question. In your nn model, why did u not add any input numbers or nodes ?

[duke_adi]

Thanks Kylie for explaining very clearly the concepts in different neural network architectures, the code part was also very interesting since I got to know for the first time about imbalanced learn library and about Dropout layer for dealing with overfitting! Besides, I guess we ran the model.evaluate before training the model to show the base case of randomly choosing between two labels yields accuracy of 0.5 (probability of random selection between two classes)?

[abtiwary]

Thank you so much for your brilliant tutorials and courses Kylie (please do more!!!)! Could you please recommend some books on the mathematics of machine learning (and books that you found useful when you dived into the subject).

[cvicracer]

Your analogy’s are awesome very easy to understand thanks

[itada-kys]

Amazing thanks :) glad to see a girl on your channel doing a tutorial for NLP !
Nice tutorial btw

[justinbyun]

Thanx @Kylie for such wonderful tut's - how original and through, I really learned A LOT!
Anyway I have a quick question, after completing evaluation with test cases - is it possible (like other ML projects) passing real life data and get the answer?
Like, we build model with 'description' and 'variety' and per given 'description' can we predict possible 'variety'?

[nitinkapoor]

I would suggest to scale the train / test data separately..

[TheAZSK]

Sorry if this sounds rude but what was the wine one for? Is it showing the accuracy of the reviews whether its high or low rated?

[suomynona]

I was hoping for one where it talks back to you as a chatbot

[okbabenattia]

Thank you so much for this amazing content, can you make another to Federated learning

[dynapilot]

how would i do for multiple class text classification?