Introduction to Deep Learning (Weeks 11)
Deep Learning represents a significant advancement in machine learning, particularly through Neural Networks, which are capable of handling complex, high-dimensional, or unstructured data more effectively than traditional methods. This chapter covers the evolution of Neural Networks from Perceptrons to Multi-Layer Perceptrons (MLPs), emphasizing key concepts such as Activation Functions, Forward Propagation, and Backpropagation. It also discusses Optimizers and provides a practical introduction to building and training MLPs using TensorFlow and Keras.
Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- Neural networks are better suited to handle complex and unstructured data compared to traditional machine learning algorithms.
- Activation functions introduce non-linearity into the network, allowing it to learn complex relationships in data.
- The processes of Forward Propagation and Backpropagation are essential for making predictions and learning from errors in neural networks.
Key Concepts
- -- Deep Learning
- A subfield of machine learning that utilizes Neural Networks to model complex patterns in high-dimensional data.
- -- Neural Networks
- Computational models inspired by the human brain that consist of interconnected groups of nodes (neurons) which process information using a connectionist approach.
- -- Activation Functions
- Mathematical equations that determine if a neuron should be activated, introducing non-linear properties to the network.
- -- Forward Propagation
- The process of passing inputs through the network to obtain an output prediction.
- -- Backpropagation
- The training algorithm for neural networks that calculates gradients to optimize weights based on prediction errors.
- -- Optimizers
- Algorithms used to adjust the weights of neural networks based on the gradients from backpropagation to minimize the loss function.
- -- TensorFlow
- An open-source machine learning library used for numerical computation and building machine learning models.
- -- Keras
- A high-level API for building and training deep learning models, running on top of TensorFlow.
Additional Learning Materials
Supplementary resources to enhance your learning experience.