## A Machine Learning oriented introduction to PALISADE, CKKS and pTensor.

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**Spoiler**: You can do math on encrypted numbers

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**Spoiler**: You can do math on encrypted numbers

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**Spoiler**: You can do math on encrypted numbers

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**Spoiler**: You can do math on encrypted numbers

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**Spoiler**: “H” is before “J”, which means that it’s the second-derivative. Obviously

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**Spoiler**: The pre-calc of ML

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**Spoiler**: Category theory has applications in machine learning

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**Spoiler**: You can do math on encrypted numbers

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**Spoiler**: “H” is before “J”, which means that it’s the second-derivative. Obviously

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**Spoiler**: The pre-calc of ML

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**Spoiler**: PyTorch offers about five ways to manipulate gradients.

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**Spoiler**: We’ve all been using randomness wrong

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**Spoiler**: Category theory has applications in machine learning

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**Spoiler**: We’ve all been using randomness wrong

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**Spoiler**: PyTorch offers about five ways to manipulate gradients.

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**Spoiler**: RTFM

** Published:**

**Spoiler**: “H” is before “J”, which means that it’s the second-derivative. Obviously

** Published:**

**Spoiler**: The pre-calc of ML

** Published:**

**Spoiler**: The pre-calc of ML

** Published:**

**Spoiler**: PyTorch offers about five ways to manipulate gradients.

** Published:**

**Spoiler**: “H” is before “J”, which means that it’s the second-derivative. Obviously

** Published:**

**Spoiler**: The pre-calc of ML

** Published:**

**Spoiler**: PyTorch offers about five ways to manipulate gradients.

** Published:**

**Spoiler**: RTFM

** Published:**

**Spoiler**: RTFM