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# Key New Features in React Router 7: Embracing the Remix Future

React Router 7 introduces powerful features from Remix and essential improvements.
Enhanced data loading with deferred components allows streaming data progressively.
Built-in server-side rendering optimizations improve performance for large applications.
Improved TypeScript integration emphasizes enhanced type safety.
Client-side data mutations provide a streamlined way to handle client-side actions.
Significant performance improvements through enhanced route prefetching.
SPA mode can be turned on or off as per requirements.
React Router 7 and Vite together bring Remix-like features to any React application.

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My First ML Pipeline: A Journey into Machine Learning Simplification

The author shares their experience of building their first machine learning (ML) pipeline.
The pipeline helps in structuring and simplifying the ML workflow, reducing complexity and ensuring consistency.
The pipeline consists of steps such as data preparation, standard scaling, and logistic regression.
The author learned the importance of modularity, reproducibility, and efficiency in ML pipelines.

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Medium

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The Counterintuitive Truth About the Single Responsibility Principle

The Single Responsibility Principle (SRP) is often misunderstood as meaning that every part of a program should do only one thing.
However, the SRP is about a larger concept than just individual functions.
It can be compared to organizing a room, where each drawer holds one type of clothing, similar to functions.
The SRP states that the entire room should be the responsibility of one person and should not contain items belonging to others.

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Prodevelopertutorial

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Introduction to Dynamic Programming with example

Dynamic programming is a method of solving problems with overlapping sub-problems and optimal substructures that can be optimised with the help of storing previously calculated solutions.
There are two approaches: top-down approach (memoization) and bottom-up approach (tabular method).
Dynamic programming can significantly reduce time complexity.
Memoization approach is a top-down approach where previously calculated solutions are stored in an array to eliminate redundancy.
The array is initialised with -1 and the values are filled for future use as required.
Tabular method is a bottom-up approach for dynamic programming where the solutions are iteratively calculated and stored in an array.
The array is filled from lower index to higher index in this case.
Memoization and tabular method have been explained using examples of generating Fibonacci numbers.
C++ programs for finding Fibonacci numbers using memoization and tabular method have been provided.
Dynamic programming is a powerful technique for optimisation of overlapping sub-problems.

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Introduction to Recursion with stack frame and recursion tree

The article explains recursion function and its implementation using a simple program in C language.
The article discusses the changes in the stack frame when using a recursion function and helps in understanding recursion tree with an example of finding the nth Fibonacci number.
It explains how local c variables are stored in the stack when a function is called with its activation record and the changes that occur when recursive calls are made.
The program uses function fun to demonstrate how the stack frame gets affected when a recursion function is used.
The recursion tree is a visual representation of recursive calls that helps in understanding the complexity of a function with multiple recursive calls.
The article also describes the pseudo code to find the nth Fibonacci number and its implementation with a recursion tree.
The article concludes with the importance of recursion in dynamic programming and backtracking and its role in getting the desired results.
Understanding recursion is important for any programmer and helps in writing efficient code with minimal errors.
Recursion can be used to solve complex problems easily by dividing the problem into simple sub-problems.
Recursion helps in developing code that is reusable and helps in reducing the complexity of code by breaking it into smaller functions.

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Prodevelopertutorial

Introduction to Brute force approach with example

Introduction to brute force approach
Understanding Brute force approach with an example
C++ program to perform brute force approach on string search
Output

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Prodevelopertutorial

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Graph data structure tutorial 10. Hamiltonian Graph

A graph that contains Hamiltonian circuit is called as Hamiltonian graph.
A path that passes through every vertex exactly once is called as Hamiltonian circuit.
If a graph has a Hamiltonian path, it means it visits all the vertices, but cannot return to the initial vertex.
Finding a Hamiltonian circuit or path is a NP complete problem.

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Graph data structure tutorial 8. Isomorphic Graph

Isomorphic Graph: Definition and Properties
Isomorphic graphs have the same number of vertices and edges.
They also have an equal number of vertices with given degrees.
Example: Graph G1 and G2 are isomorphic, while G1 and G3 are not.

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Medium

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Scala Factory Pattern - Every Engineer’s Favorite Way to Store Objects

Scala Factory Pattern is widely used by engineers to store objects for ease of its creation.
The blog covers various topics like Types of Factory Patterns, Components of the Factory Pattern, Scala-Specific considerations, and Advanced topics.
Scala Factory Pattern comprises of three types of patterns: Simple Factory, Factory Method, and Abstract Factory.
FastFoodFactory represents a fast food joint that creates products such as a Burger or Pizza based on the client's order.
In Factory Method, the chefs are responsible for preparing the customers' dish based on specifications like spicy or sweaty dishes.
Abstract Factory is for clients seeking a cohesive set of products that pair well together. Each factory is prepared by a different chef.
Factory Pattern's Components are the product interface, concrete products, factory interface, concrete factory, and the client.
Scala enthusiasts can use Singleton objects to ensure that no matter how many times they request products, they get the same factory.
Scala's Trait is used to ensure that factory interfaces are flexible and mixable, making it simple to expand them later.
Scala's pattern matching assists in serving the right product quickly and efficiently and avoiding mixed Factory and Product roles.

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Dev

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Mastering Concurrent Control in GoFrame with gmlock

GoFrame's gmlock package provides concurrent control, making it easier to handle race conditions in Go applications.
Concurrent control is essential to avoid oversold products, inconsistent inventory counts, unhappy customers, and stressed-out dev teams.
gmlock offers simple locking, read-write locking, and try-locking with timeouts, providing effective solutions for concurrent access control.
Real-world examples include protecting user balance updates and safe configuration updates.

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Medium

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Programming vs. Coding vs. Development: What’s the Difference?

Coding is the lowest level of interaction with computers, consisting of creating instructions with a language that computers can read.
Coders focus on syntax and language rules of programming languages, as well as basic debugging.
Coding serves as the foundation for more complex concepts like programming and development.
Programming encompasses a broader understanding of system architecture and the entire application, going beyond coding.

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Dev

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Tips to learn python

Understanding the Basics: Learn Python's syntax, semantics, and indentation rules.
Using Interactive Tools: Utilize Python REPL and Jupyter Notebooks for experimentation.
Following a Structured Course: Take online courses or refer to books for structured learning.
Practicing Regularly: Solve coding challenges and work on small projects to apply your knowledge.
Learning Libraries and Frameworks: Familiarize yourself with the Python standard library and popular libraries for specific tasks.
Joined Community: Engage with communities like Reddit, Stack Overflow, and Python.org.
Explore Documentation: Refer to the official Python documentation for comprehensive explanations.
Practiced Debugging: Use debugging tools and IDEs with integrated features.
Used Version Control: Learn Git for version control and collaboration on projects.
Bonus: Consistency is key, code daily and regularly review your progress.

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Prodevelopertutorial

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Graph data structure tutorial 3. Graph Representation Adjacency List

Introduction: In this chapter, we will learn about representing a graph using adjacency lists.
Representation in Linked List: Linked Lists are used to represent the adjacency lists in this method.
Now why do we use Linked List to represent Adjacency Lists: Linked Lists allow for easy addition and deletion of vertices or edges.
Implementation of Graph Representation using Adjacency Lists using C++: The code demonstrates the implementation of a graph using adjacency lists in C++.

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Graph data structure tutorial 2. Graph Representation Adjacency Matrix

Introduction to graph representation using adjacency matrix
Understanding of graph representation with an example
Implementation of graph representation using adjacency matrix using C++
Output of the adjacency matrix implementation

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Prodevelopertutorial

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Graph data structure tutorial 1. Graph Introduction

Graph is a non-linear data structure made up of nodes/vertices and edges.
It does not have a root node and can be traversed in any direction.
A graph consists of vertices and edges, and can be directed or undirected.
Graphs are used for various purposes like finding minimum distance between cities, connecting places in a map, and in social media.

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