Activation functions play a crucial role in neural networks. Let’s dive into their purpose and impact:

1. Purpose of Activation Functions:
   • Non-Linearity: Activation functions introduce non-linearity to the network. Without them, the neural network would behave like a linear regression model, limiting its ability to capture complex data patterns.
   • Complex Phenomena: Non-linearity allows neural networks to approximate intricate functions. This enables tasks like language processing, image recognition, and time series predictions.
2. Impact on Learning Complex Patterns:
   • Transforming Data: Neural networks classify data that isn’t linearly separable. Activation functions transform data, making the resulting points linearly separable. This transformation enables the network to learn complex patterns.
   • Representation Power: By introducing non-linearity, activation functions allow neural networks to represent and learn intricate features, making them more adaptable to real-world phenomena.

A graph is a non-linear data structure composed of vertices (also known as nodes) connected by edges. It’s used to represent relationships between entities. Here’s a brief overview:

1. Graph Representation:
   • Vertices: Fundamental units of the graph.
   • Edges: Connect two nodes.
   • Directed Graph: Edges have a direction.
   • Undirected Graph: Edges are bidirectional.
2. Common Graph Traversal Methods:
   • Depth First Search (DFS):
     • Starts at a node and explores as far as possible along each branch before backtracking
     • Implemented using a stack or recursion.
     • Useful for finding connected components, topological sorting, and cycle detection.
   • Breadth First Search (BFS):
     • Traverses level by level, exploring neighbor nodes at each level
     • Implemented using a queue.
     • Useful for shortest path, connected components, and network analysis.

RPSC(Rajasthan Public Service Commission)

The Rajasthan Public Service Commission (RPSC) conducts competitive examinations for various government posts in the state of Rajasthan. Here’s an overview of the RPSC exam stages:

1. Preliminary Examination (Stage 1):
   • Unlike the UPSC IAS Exam, RPSC RAS has only one paper in the preliminary stage.
   • It consists of 150 objective questions, carrying a total of 200 marks.
   • The duration of the prelims exam is 3 hours.
2. Mains Examination (Stage 2):
   • There are four theory papers in the RAS Mains, each worth 200 marks.
   • Candidates are tested on various subjects relevant to the position they are applying for.
3. Personality Test/Interview (Stage 3):
   • The interview carries a total of 100 marks.
   • It assesses the candidate’s personality, communication skills, and suitability for the role.

1. List:
   • Represents an ordered collection (also known as a sequence) where elements can be accessed by their position in the list.
   • Allows duplicate elements and maintains the order in which elements are inserted.
   • Common implementations include Array List and LinkedList.
   • Lists are used when the order of elements matters, and duplicates are allowed.
2. Set:
   • Represents a collection that does not allow duplicate elements.
   • It is unordered, meaning it doesn’t maintain the insertion order of elements.
   • Common implementations include HashSet, Tree Set, and Linked HashSet.
   • Sets are useful when emphasizing uniqueness without any specific order.