Merge branch 'main' into issues

Author: ajay-dhangar

docs/Deep Learning/Multilayer Perceptron (MLP).md

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+---
+id: multilayer-perceptron-in-deep-learning
+title: Multilayer Perceptron in Deep Learning
+sidebar_label: Introduction to Multilayer Perceptron (MLP)
+sidebar_position: 5
+tags: [Multilayer Perceptron, MLP, deep learning, neural networks, machine learning, supervised learning, classification, regression]
+description: In this tutorial, you will learn about Multilayer Perceptron (MLP), its architecture, its applications in deep learning, and how to implement MLP models effectively for various tasks.
+---
+
+### Introduction to Multilayer Perceptron (MLP)
+A Multilayer Perceptron (MLP) is a type of artificial neural network used in deep learning. It consists of multiple layers of neurons, including an input layer, one or more hidden layers, and an output layer. MLPs are capable of learning complex patterns and are used for various tasks, including classification and regression.
+
+### Architecture of Multilayer Perceptron
+An MLP is composed of:
+
+- **Input Layer**: The first layer that receives the input features. Each neuron in this layer corresponds to a feature in the input data.
+- **Hidden Layers**: Intermediate layers between the input and output layers. Each hidden layer contains neurons that apply activation functions to the weighted sum of inputs.
+- **Output Layer**: The final layer that produces the predictions. The number of neurons in this layer corresponds to the number of classes (for classification) or the number of output values (for regression).
+
+**Activation Functions**: Non-linear functions applied to the weighted sum of inputs in each neuron. Common activation functions include ReLU (Rectified Linear Unit), sigmoid, and tanh.
+
+**Forward Propagation**: The process of passing input data through the network to obtain predictions.
+
+**Backpropagation**: The process of updating weights in the network based on the error of predictions, using gradient descent or its variants.
+
+### Example Applications of MLP
+- **Image Classification**: Classifying images into different categories (e.g., identifying objects in photos).
+- **Text Classification**: Categorizing text into predefined classes (e.g., spam detection).
+- **Regression Tasks**: Predicting continuous values (e.g., house prices based on features).
+
+### Advantages of Multilayer Perceptron
+- **Ability to Learn Non-Linear Relationships**: Through activation functions and multiple layers, MLPs can model complex non-linear relationships.
+- **Flexibility**: Can be used for both classification and regression tasks.
+- **Generalization**: Capable of generalizing well to new, unseen data when properly trained.
+
+### Disadvantages of Multilayer Perceptron
+- **Training Time**: MLPs can be computationally expensive and require significant time and resources to train, especially with large datasets and many layers.
+- **Overfitting**: Risk of overfitting, especially with complex models and limited data. Regularization techniques like dropout and weight decay can help mitigate this.
+- **Vanishing Gradient Problem**: During backpropagation, gradients can become very small, slowing down learning. This issue is lessened with modern activation functions and architectures.
+
+### Practical Tips for Implementing MLP
+
+- **Feature Scaling**: Normalize or standardize input features to improve the convergence of the training process.
+- **Network Architecture**: Experiment with the number of hidden layers and neurons per layer to find the optimal network architecture for your task.
+- **Regularization**: Use dropout, L2 regularization, and early stopping to prevent overfitting and improve generalization.
+- **Hyperparameter Tuning**: Adjust learning rates, batch sizes, and other hyperparameters to enhance model performance.
+
+### Example Workflow for Implementing an MLP
+
+1. **Data Preparation**:
+    - Load and preprocess data (e.g., normalization, handling missing values).
+    - Split data into training and testing sets.
+
+2. **Define the MLP Model**:
+    - Specify the number of layers and neurons in each layer.
+    - Choose activation functions for hidden layers and output layers.
+
+3. **Compile the Model**:
+    - Select an optimizer (e.g., Adam, SGD) and a loss function (e.g., cross-entropy for classification, mean squared error for regression).
+    - Define evaluation metrics (e.g., accuracy, F1 score).
+
+4. **Train the Model**:
+    - Fit the model to the training data, specifying the number of epochs and batch size.
+    - Monitor training and validation performance to prevent overfitting.
+
+5. **Evaluate the Model**:
+    - Assess model performance on the testing set.
+    - Generate predictions and analyze results.
+
+6. **Tune and Optimize**:
+    - Adjust hyperparameters and model architecture based on performance.
+    - Use techniques like grid search or random search for hyperparameter optimization.
+
+### Implementation Example
+
+Here’s a basic example of how to implement an MLP using TensorFlow and Keras in Python:
+
+```python
+import numpy as np
+import tensorflow as tf
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.layers import Dense
+from sklearn.model_selection import train_test_split
+from sklearn.preprocessing import StandardScaler
+from sklearn.datasets import load_iris
+
+# Load and prepare data
+data = load_iris()
+X = data.data
+y = data.target
+
+# Standardize features
+scaler = StandardScaler()
+X_scaled = scaler.fit_transform(X)
+
+# Split data
+X_train, X_test, y_train, y_test = train_test_split(X_scaled, y, test_size=0.2, random_state=42)
+
+# Define MLP model
+model = Sequential([
+    Dense(64, activation='relu', input_shape=(X_train.shape[1],)),
+    Dense(32, activation='relu'),
+    Dense(3, activation='softmax')  # Number of classes in the output layer
+])
+
+# Compile the model
+model.compile(optimizer='adam',
+              loss='sparse_categorical_crossentropy',
+              metrics=['accuracy'])
+
+# Train the model
+model.fit(X_train, y_train, epochs=50, batch_size=32, validation_split=0.2)
+
+# Evaluate the model
+loss, accuracy = model.evaluate(X_test, y_test)
+print(f'Test Accuracy: {accuracy:.2f}')
+```
+
+### Performance Considerations
+
+#### Computational Resources
+- **Training Time**: Training MLPs can be time-consuming, especially with large datasets and complex models. Using GPUs or TPUs can accelerate training.
+- **Memory Usage**: Large networks and datasets may require significant memory. Ensure your hardware can handle the computational load.
+
+#### Model Complexity
+- **Number of Layers and Neurons**: More layers and neurons can increase model capacity but may also lead to overfitting. Find a balance that suits your data and task.
+
+### Conclusion
+Multilayer Perceptrons (MLPs) are fundamental to deep learning, providing powerful capabilities for learning complex patterns in data. By understanding MLP architecture, advantages, and practical implementation tips, you can effectively apply MLPs to various tasks in machine learning and deep learning projects.

docs/Jekyll/01-Introduction.md

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+---
+id: introduction-to-jekyll
+title: Introduction to Jekyll
+sidebar_label: Introduction to Jekyll
+sidebar_position: 1
+tags: [jekyll, static site generator]
+description: Learn about Jekyll, a static site generator used for creating fast and secure websites with ease.
+---
+
+Jekyll is a static site generator written in Ruby. It takes a directory of templates, content files, and configuration, and produces a static website. Jekyll is commonly used for blogs and project websites because of its simplicity and efficiency.
+
+### Key Features of Flask
+
+1. **Static Site Generation:** Jekyll generates static HTML pages, which are fast to load and secure.
+
+2. **Markdown Support:** Write content in Markdown, and Jekyll will convert it to HTML.
+
+3. **Template System:** Use Liquid templates to create dynamic content.
+
+4. **Plugins:** Extend Jekyll's functionality with plugins.
+
+
+### Conclusion
+
+Jekyll is an excellent choice for creating simple, fast, and secure static websites. Its features make it suitable for personal blogs, project documentation, and more. Whether you're a developer looking to build a portfolio or a content creator needing a reliable blogging platform, Jekyll offers the tools and flexibility needed to create a professional and efficient website.

docs/Jekyll/02-Installation.md

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+---
+id: installing-jekyll
+title: Installing Jekyll
+sidebar_label: Installing Jekyll
+sidebar_position: 2
+tags: [jekyll, installation]
+description: Learn how to install Jekyll on your local machine and get started quickly.
+---
+
+Installing Jekyll is straightforward, especially if you have Ruby installed on your system. Jekyll requires a few dependencies and can be set up with simple commands.
+
+### Prerequisites
+**Ruby:** Ensure you have Ruby installed. You can check by running `ruby -v` in your terminal.
+
+**RubyGems:** This is usually installed with Ruby. Check with `gem -v`.
+
+### Installation Steps
+
+1. **Install Jekyll and Bundler:**
+```sh
+gem install jekyll bundler
+```
+
+2. **Verify the Installation:**
+```sh
+jekyll -v
+```
+### Conclusion
+
+By following these steps, you should have Jekyll installed on your system, ready to create and manage static websites. With Jekyll and Bundler set up, you can efficiently handle dependencies and ensure your site builds consistently across different environments.

docs/Jekyll/03-Setting-Up.md

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+---
+id: setting-up-a-new-jekyll-site
+title: Setting up a new Jekyll site
+sidebar_label: Setting up a new Jekyll site
+sidebar_position: 3
+tags: [jekyll, setup, new site]
+description: Learn how to set up a new Jekyll site from scratch, including creating and structuring your project.
+---
+
+Setting up a new Jekyll site is simple and quick, allowing you to get started with your static website in no time. Jekyll provides a default structure that you can easily customize.
+
+### Steps
+
+1. **Create a New Jekyll Site:**
+```sh
+jekyll new my-awesome-site
+cd my-awesome-site
+```
+
+2. **Build the Site and Serve Locally:**
+```sh
+bundle exec jekyll serve
+```
+Visit `http://localhost:4000` to see your new site.
+
+### Conclusion
+
+With these steps, you've created a new Jekyll site and served it locally, ready for customization and content addition. Jekyll's default structure includes folders for posts, pages, assets, and configuration, making it easy to organize and manage your site effectively.

docs/Jekyll/04-Configuration.md

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+---
+id: jekyll-configuration
+title: Jekyll Configuration
+sidebar_label: Jekyll Configuration
+sidebar_position: 4
+tags: [jekyll, configuration]
+description: Learn how to configure your Jekyll site using the `_config.yml` file to customize settings and behavior.
+---
+
+Jekyll uses a `_config.yml` file for configuration, where you can set various options for your site. This file is essential for customizing your site's behavior, appearance, and functionality.
+
+### Key Configuration Options
+
+1. **Site Settings:**
+``yaml
+title: My Awesome Site
+description: >- # this means to ignore newlines until "baseurl:"
+  This is my awesome website built with Jekyll.
+baseurl: "" # the subpath of your site, e.g. /blog
+url: "http://example.com" # the base hostname & protocol for your site
+```
+
+2. **Build Settings:**
+```yaml
+markdown: kramdown
+theme: minima
+plugins:
+  - jekyll-feed
+```
+
+### Conclusion
+
+The `_config.yml` file is crucial for customizing your Jekyll site. By modifying this file, you can easily change the behavior and appearance of your site. Whether you need to update the site title, add plugins, or adjust markdown settings,` _config.yml` provides a centralized location for these configurations, simplifying site management and customization.

docs/Jekyll/05-Pages-and-Post.md

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+---
+id: creating-pages-and-posts
+title: Creating Pages and Posts
+sidebar_label: Creating Pages and Posts
+sidebar_position: 5
+tags: [jekyll, pages, posts]
+description: Learn how to create pages and posts in Jekyll to add content to your site.
+---
+
+Creating content in Jekyll involves creating pages and posts. Pages are used for static content, while posts are typically used for blog entries.
+
+### Creating Pages
+
+1. **Create a New Page:**
+```sh
+touch about.md
+```
+- Add the following front matter to the page:
+
+markdown
+---
+layout: page
+title: About
+permalink: /about/
+---
+
+
+2. **Add Content:**
+
+markdown
+# About Me
+This is the about page of my Jekyll site.
+
+
+### Creating Posts
+
+1. **Create a New Post:**
+```sh
+touch _posts/2024-07-20-my-first-post.md
+```
+
+- Add the following front matter to the post:
+
+```markdown
+---
+layout: post
+title: "My First Post"
+date: 2024-07-20 12:00:00 -0400
+categories: blog
+---
+```
+
+2. **Add Content:**
+
+```markdown
+# Welcome
+This is my first blog post on my new Jekyll site.
+```
+
+### Conclusion
+
+Creating pages and posts in Jekyll is straightforward. By using the appropriate front matter, you can easily add and organize content on your site. Whether you're building a blog, a portfolio, or a documentation site, Jekyll's simple file-based structure makes content management intuitive and efficient.

docs/Jekyll/06-Themes.md

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+---
+id: using-themes
+title: Using Themes
+sidebar_label: Using Themes
+sidebar_position: 6
+tags: [jekyll, themes]
+description: Learn how to use and customize themes in Jekyll to enhance the look and feel of your site.
+---
+
+Jekyll themes allow you to quickly change the appearance of your site without having to design it from scratch. Themes provide a consistent look and feel across all pages and posts.
+
+### Steps to Use a Theme
+
+1. **Choose a Theme:** Browse themes on Jekyll Themes or GitHub.
+
+2. **Add the Theme to Your Site:**
+
+```yaml
+# _config.yml
+theme: jekyll-theme-minimal
+```
+
+3. **Install the Theme:**
+```sh
+bundle install
+```
+
+### Customizing a Theme
+
+To customize a theme, you can override theme files by copying them into your site’s directory. For example, to customize the `_layouts/default.html` layout, copy it from the theme's gem to your local `_layouts` directory.
+
+### Conclusion
+
+Using themes in Jekyll simplifies the process of styling your site. You can quickly implement a professional design and further customize it to meet your needs, ensuring your site looks unique and polished.