Deep Learning With TF 2.0: 02.00- Linear Algebra
- 02.00 - Linear Algebra
- 02.01 - Scalars, Vectors, Matrices and Tensors
- 02.02 - Multiplying Matrices and Vectors
- 02.03 - Identity and Inverse Matrices
- 02.04 - Linear Dependence and Span
- 02.05 - Norms
- 02.06 - Special Kinds of Matrices and Vectors
- 02.07 - Eigendecomposition
- 02.08 - Singular Value Decomposition
- 02.09 - The Moore-Penrose Pseudoinverse
- 02.10 - The Trace Operator
- 02.11 - The Determinant
- 02.12 - Example: Principal Components Analysis
Computer Vision: Basic Image Processing
- Why do we need to process images?
- Where are the source of errors and image defects?
- How can we improve low image contrast?
- How do we evaluate the tone transfer in an image?
- How do we improve the contrast in an image?
- What can we use when linear correction can’t be applied?
- How can we treat noisy images?
- How are Filter Kernels used for Image Processing?
- What is Edge Detection?
- What is a Canny Edge Detector?
Blog Categories
Recent posts
- 30 Jun 2019 Computer Vision: Object Detection
- 23 Jun 2019 Deep Learning With TF 2.0: 04.00- Numerical Computation
- 16 Jun 2019 Computer Vision: Face Recognition
- 09 Jun 2019 Computer Vision: Image Retrieval
- 02 Jun 2019 Deep Learning With TF 2.0: 03.00- Probability and Information Theory