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Introduction to Neural Networks

1. Concept of Neural Network

First, we will discuss what a neural network is and how it works. And also consider the scope of its application.

What is a Neural Network?

Neural Network Structure

What is a Neuron?

Activation Functions

Forward and Backward Propagation

Applications of Deep Learning in the Real World

2. Neural Network from Scratch

Next, we will try to build our own neural network and see how efficiently it copes with learning. We will also consider a ready-made solution from the scikit-learn library.

Single Neuron Implementation

Model Training and Evaluation

Neural Network with scikit-learn

3. Conclusion

Finally, we will give you some additional useful information on how to understand which model to use and what types of neural networks there are. To complete the course, you will be tested on your acquired knowledge.

Neural Networks or Traditional Models

Other types of Neural Networks

Manual Hyperparameter Tuning

Automatic Hyperparameter Tuning

Final Quiz

Summary

Final Quiz

1. A neuron in a neural network typically:

2. A perceptron is:

3. The primary role of Backward Propagation is:

4. Scaling training data:

5. The process of training a neural network primarily involves:

6. TensorFlow and PyTorch are:

7. When would you choose traditional machine learning models over neural networks?

8. Convolutional Neural Networks (CNNs) are primarily used for:

9. Recurrent Neural Networks (RNNs) are best suited for:

10. Which of the following is NOT an advantage of using neural networks?

11. What role does an activation function play in a neuron?

12. Which phase involves calculating the loss and then adjusting the weights backwards through the layers?

13. In the context of neural networks, epochs refer to:

14. An overfitted neural network:

A neuron in a neural network typically:

Selecciona la respuesta correcta

Transmits electrical signals.

Receives inputs and produces an output based on them.

Can learn without any input.

Only exists in biological systems.

A perceptron is:

Selecciona la respuesta correcta

A neural network with a single layer.

Another name for neuron.

A type of activation function.

A cloud storage solution.

The primary role of Backward Propagation is:

Selecciona la respuesta correcta

Predicting the next sequence in data.

Adjusting weights in the neural network based on errors.

Filtering out noise from the input.

Storing the results of forward propagation.

Scaling training data:

Selecciona la respuesta correcta

Makes the data unreadable.

Can help improve the speed and accuracy of training neural networks.

Is only necessary for traditional machine learning models.

Introduces more noise into the data.

The process of training a neural network primarily involves:

Selecciona la respuesta correcta

Randomly setting all weights and biases.

Avoiding the use of activation functions.

Iteratively adjusting weights to minimize error.

Only using forward propagation.

TensorFlow and PyTorch are:

Selecciona la respuesta correcta

Libraries/frameworks for deep learning.

Types of activation functions.

Methods of backward propagation.

Specific types of neural networks.

When would you choose traditional machine learning models over neural networks?

Selecciona la respuesta correcta

When dealing with image recognition.

When you have small datasets and simpler patterns.

In tasks requiring sequence predictions only.

Convolutional Neural Networks (CNNs) are primarily used for:

Selecciona la respuesta correcta

Text data without sequence.

Tabular data.

One-dimensional data only.

Image data.

Recurrent Neural Networks (RNNs) are best suited for:

Selecciona la respuesta correcta

Image classification.

Tabular data analysis.

Sequential data like time series or text.

Static data without any order.

Which of the following is NOT an advantage of using neural networks?

Selecciona la respuesta correcta

Can recognize complex patterns.

Can handle large datasets.

Always provides interpretable results.

What role does an activation function play in a neuron?

Selecciona la respuesta correcta

Helps in storing data.

Assists in backward propagation.

Introduces flexibility to the model.

Reduces the number of parameters.

Which phase involves calculating the loss and then adjusting the weights backwards through the layers?

Selecciona la respuesta correcta

Initialization

Regularization

Backward Propagation

Forward Propagation

In the context of neural networks, epochs refer to:

Selecciona la respuesta correcta

The maximum depth of a network.

The number of neurons.

The number of times the entire dataset is passed through the network.

The learning rate of a network.

An overfitted neural network:

Selecciona la respuesta correcta

Performs very well on the training data but poorly on new, unseen data.

Performs poorly on both training and test data.

Performs well on unseen data but poorly on the training data.

¿Todo estuvo claro?

Sección 3. Capítulo 5

Contenido del Curso

Introduction to Neural Networks

1. Concept of Neural Network

What is a Neural Network?Neural Network Structure What is a Neuron?Activation Functions Forward and Backward Propagation Applications of Deep Learning in the Real World

2. Neural Network from Scratch

Single Neuron Implementation Perceptron Layers Forward Propagation Backward Propagation Data Preprocessing Model Training and Evaluation Neural Network with scikit-learn

3. Conclusion

Neural Networks or Traditional Models Other types of Neural Networks Manual Hyperparameter Tuning Automatic Hyperparameter Tuning Final Quiz Summary

Introduction to Neural Networks

Final Quiz

1. A neuron in a neural network typically:

2. A perceptron is:

3. The primary role of Backward Propagation is:

4. Scaling training data:

5. The process of training a neural network primarily involves:

6. TensorFlow and PyTorch are:

7. When would you choose traditional machine learning models over neural networks?

8. Convolutional Neural Networks (CNNs) are primarily used for:

9. Recurrent Neural Networks (RNNs) are best suited for:

10. Which of the following is NOT an advantage of using neural networks?

11. What role does an activation function play in a neuron?

12. Which phase involves calculating the loss and then adjusting the weights backwards through the layers?

13. In the context of neural networks, epochs refer to:

14. An overfitted neural network:

A neuron in a neural network typically:

Selecciona la respuesta correcta

Transmits electrical signals.

Receives inputs and produces an output based on them.

Can learn without any input.

Only exists in biological systems.

A perceptron is:

Selecciona la respuesta correcta

A neural network with a single layer.

Another name for neuron.

A type of activation function.

A cloud storage solution.

The primary role of Backward Propagation is:

Selecciona la respuesta correcta

Predicting the next sequence in data.

Adjusting weights in the neural network based on errors.

Filtering out noise from the input.

Storing the results of forward propagation.

Scaling training data:

Selecciona la respuesta correcta

Makes the data unreadable.

Can help improve the speed and accuracy of training neural networks.

Is only necessary for traditional machine learning models.

Introduces more noise into the data.

The process of training a neural network primarily involves:

Selecciona la respuesta correcta

Randomly setting all weights and biases.

Avoiding the use of activation functions.

Iteratively adjusting weights to minimize error.

Only using forward propagation.

TensorFlow and PyTorch are:

Selecciona la respuesta correcta

Libraries/frameworks for deep learning.

Types of activation functions.

Methods of backward propagation.

Specific types of neural networks.

When would you choose traditional machine learning models over neural networks?

Selecciona la respuesta correcta

When dealing with image recognition.

When you have small datasets and simpler patterns.

In tasks requiring sequence predictions only.

Convolutional Neural Networks (CNNs) are primarily used for:

Selecciona la respuesta correcta

Text data without sequence.

Tabular data.

One-dimensional data only.

Image data.

Recurrent Neural Networks (RNNs) are best suited for:

Selecciona la respuesta correcta

Image classification.

Tabular data analysis.

Sequential data like time series or text.

Static data without any order.

Which of the following is NOT an advantage of using neural networks?

Selecciona la respuesta correcta

Can recognize complex patterns.

Can handle large datasets.

Always provides interpretable results.

What role does an activation function play in a neuron?

Selecciona la respuesta correcta

Helps in storing data.

Assists in backward propagation.

Introduces flexibility to the model.

Reduces the number of parameters.

Which phase involves calculating the loss and then adjusting the weights backwards through the layers?

Selecciona la respuesta correcta

Initialization

Regularization

Backward Propagation

Forward Propagation

In the context of neural networks, epochs refer to:

Selecciona la respuesta correcta

The maximum depth of a network.

The number of neurons.

The number of times the entire dataset is passed through the network.

The learning rate of a network.

An overfitted neural network:

Selecciona la respuesta correcta

Performs very well on the training data but poorly on new, unseen data.

Performs poorly on both training and test data.

Performs well on unseen data but poorly on the training data.

¿Todo estuvo claro?

Sección 3. Capítulo 5