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1 | 1 | # 🐍 AI Deep Learning TensorFlow Python 🐍 |
2 | 2 | 🐍 **Deep Learning** with **TensorFlow** 🐍 |
3 | 3 |
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4 | | -Learning **Deep Learning** with the Tutorials from Sentdex and Siraj Raval.</br> |
5 | | -Link(Sentdex): https://pythonprogramming.net/introduction-deep-learning-python-tensorflow-keras/ </br> |
6 | | -Link(Siraj Raval): https://www.youtube.com/watch?v=2FmcHiLCwTU |
| 4 | +Learning **AI Deep Learning** / **Machine Learning**.</br> |
7 | 5 |
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8 | 6 | ## What is a neural network? |
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10 | 8 | A basic **neural network** consists of an **input layer**, which is just **your data, in numerical form**. After your **input layer**, you will have some number of what are called **"hidden" layers**. **A hidden layer** is just in between your input and output layers.</br> ***One hidden layer means you just have a neural network. Two or more hidden layers? you've got a deep neural network!*** |
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12 | 10 |  |
| 11 | + |
| 12 | +## What is a Tensor? |
| 13 | + |
| 14 | +Each operation takes a **Tensor** as an Input and outputs a **Tensor**.</br> |
| 15 | +A **Tensor** is how Data is represented in **TensorFlow**.</br> |
| 16 | +A **Tensor is a multidimensional array** ex: </br> |
| 17 | +([0.245,0.618,0.723], </br>[0.245,0.618,0.723], </br>[0.245,0.618,0.723]). </br> |
| 18 | +This would be a **normalized three-way-tensor**.</br> |
| 19 | +**normalized** in **TensorFlow** means that the numbers are converted to a value between 0 and 1. The Data needs to be normalized, to be actually useable in **TensorFlow**. |
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| 22 | + |
| 23 | +## Resources & Links: |
| 24 | +Deep Learning: https://pythonprogramming.net/introduction-deep-learning-python-tensorflow-keras/ </br> |
| 25 | +TensorFlow Overview: https://www.youtube.com/watch?v=2FmcHiLCwTU |
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