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Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial

Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial

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.
🎥 YouTube: https://youtube.com/ycubed
🐦 Twitter: https://twitter.com/kylieyying
📷 Instagram: https://instagram.com/kylieyying/

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

⭐️ Resources ⭐️
💻 Datasets: https://drive.google.com/drive/folders/1YnxDqNIqM2Xr1Dlgv5pYsE6dYJ9MGxcM?usp=sharing
💻 Feedforward NN colab notebook: https://colab.research.google.com/drive/1UxmeNX_MaIO0ni26cg9H6mtJcRFafWiR?usp=sharing
💻 Wine review colab notebook: https://colab.research.google.com/drive/1yO7EgCYSN3KW8hzDTz809nzNmacjBBXX?usp=sharing

⭐️ 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)

🎉 Thanks to our Champion and Sponsor supporters:
👾 Raymond Odero
👾 Agustín Kussrow
👾 aldo ferretti
👾 Otis Morgan
👾 DeezMaster

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Comments (21)

  1. Thanks for watching everyone! I hope you enjoy learning from the examples in this course 🙂

  2. Hi my sweet can I call for you

  3. 1:43:41 My graphs already looked fine ?

  4. Will check later. Looks great

  5. thanks for the tutorial 👏👏

  6. Lopez Amy Gonzalez Jessica Johnson Jessica

  7. 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)

  8. This is a really nice intro course, very well designed. Kylie is so smart, speaks so clearly, explains clearly and plainly, and even a really good typist. I look forward to more tutorials from Kylie.

  9. Solution to the hub layers probleb:

    model = tf.keras.Sequential([
    tf.keras.layers.Lambda(lambda x: hubs_layer(x)),
    tf.keras.layers.Dense(16, activation='relu'),
    tf.keras.layers.Dense(16, activation='relu'),
    tf.keras.layers.Dense(1, activation='sigmoid')
    ])

    In a nutshell HUB is recognized as a keras layer so you have t turn it into one

  10. the way she explained backprop is so mind blowing! loved it

  11. thanks amazing teacher

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

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

  14. Great course.

  15. I like the last tutorial. I got Accuracy : 85 % with logistic regression so I wonder whetever model selection is more important then just using neurals

  16. keren banget mbakkk

  17. How the hell you do to write at two places at the same time ? which trick do you use ?

  18. Does anyone follow along and encounter error while creating the model? It says, "Only instances of 'keras.Layer' can be added to Sequential model…
    Thank you

  19. Thank you so much Kylie!

  20. @1:34:08 I get this error: Failed to convert a NumPy array to a Tensor (Unsupported object type float). Can't convert strings to floats, and I am using Excel file instead of csv file. I did try to convert my Excel file to csv but that didn't work.

    Not sure why your NumPy array gets coverted to Tensor and mine doesn't

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