**Table of Contents:**

- Installation
- Version Check
- Array Initialization ~ 1-D, 2-D, 3-D
- Generating Data
- Vector Arrangements
- Data-Type — Conversions
- Math Operations
- Dot Product
- Matrix Multiplication
- Indexing and Slicing (2-D)
- Indexing and Slicing (2-D — Matrix)
- Reshaping and Transpose axes
- Concatenation
- Summing across axes
- Mean across axes
- Dimension Expansion & moving axes.
- Max (Min) and Argmax
- Slicing and Indexing (3-D Matrix)

**1. Introduction**

**2. Version Check**

**3. Array Initialization ~ 1-D, 2-D, 3-D **

**Scalar and 1-D Array**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**2-D Vector Array**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**4. Generating Data**

**Scalar and 1-D Array**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**Draw random samples from the Normal distribution**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**Draw samples from the uniform distribution**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**5. Vector Arrangements**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**6. Data-Type — Conversions**

**uint8/16/32/64 ← → float8/16/32/64**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**7. Math Operations**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**8. Dot Product**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**9. Matrix Multiplication**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**10. Indexing and Slicing (2-D)**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**11. Indexing and Slicing (2-D — Matrix)**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**12. Reshaping and Transpose axes**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**13. Concatenation**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**14. Summing across axes**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**15. Mean across axes**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**16. Dimension Expansion & moving axes**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**17. Max (Min) and Argmax**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

**18. Slicing and Indexing (3-D Matrix)**

**Numpy Implementation:**

**TensorFlow Implementation:**

**Torch Implementation:**

Due to visualization constraints, I skipped the operations on the higher dimension parts.

I hope I was able to provide some visual understanding to some of the fundamental operations along with your choice of deep learning framework and I will add more detailed operations shortly.

Check out the Notebooks that contains the entire code implementation and feel free to break it.

Complete Code Implementation is available at,

Until then, see you next time.

Categories: Machine Learning, Deep Learning , Tags: #AI, #deepscopy