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Week 2 - Introduction to TensorFlow,Part I

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This week you will...

  • get a soft introduction to what Machine Learning and Deep Learning are, and how they offer you a new programming paradigm, giving you a new set of tools to open previously unexplored scenarios. All you need to know is some very basic programming skills, and you'll pick the rest up as you go along.

  • take the just learned new programming paradigm used in machine learning to the next level by beginning to solve problems of computer vision with just a few lines of code!

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Learning Resources

  • (Fireship, 2:30 min)

  • (IBM Technology, 10 min)

  • (3Blue1Brown, 13 min)

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Until next week you should...

  • Watch the following videos:

    • (StatQuest Video, 6 min)

      • The video is mandatory

(Pankaj Kumar Porwal, 5:40 min)
  • (Galaxy Inferno Codes, 5:40 min)

  • (Aladdin Persson, 21 min)

  • (Aladdin Persson, 11 min)

  • The accompanying notebook is optional

  • (StatQuest, 7 min)

  • (StatQuest, 7 min)

  • (DigitalSreeni, 10 min)

  • Decide on a project for the course and form groups

  • Complete the two assignments in the following notebooks:

  • file-pdf
    526KB
    251030_Introduction_Part_I.pdf
    PDF
    arrow-up-right-from-squareOpen
    Machine Learning Explained in 100 Secondsarrow-up-right
    What is a Loss Function? Understanding How AI Models Learnarrow-up-right
    Backpropagation, intuitively | Deep Learning Chapter 3arrow-up-right
    Cross Validationarrow-up-right
    Parameters vs Hyperparametersarrow-up-right
    Validation data: How it works and why you need itarrow-up-right
    TensorFlow Tutorial 3 - Neural Networks with Sequential and Functional APIarrow-up-right
    TensorFlow Tutorial 14 - Callbacks with Keras and Writing Custom Callbacksarrow-up-right
    Bias and Variance (Overfitting)arrow-up-right
    Model Evaluation (Confusion Matrix)arrow-up-right
    Callback Functions in TensorFlowarrow-up-right
    Assignment Notebook 1arrow-up-right
    Assignment Notebook 2arrow-up-right