ipsitadhar

Story Points don't work. Even Ron Jeffries, who invented them, said he was sorry years ago. And not only did he apologize, but he called the whole estimation idea "Evil." Unfortunately, too many teams still use these points to estimate their work. Story Points is a made-up metric to estimate work effort, not time. The goal was to prevent management from misusing estimates. But it didn't work. Every team I've ever met keeps a conversion table to translate back and forth between points and time. Some will never admit it, but go and talk to the folks doing the work. Look at me and tell me I'm wrong. But it gets worse: Teams use points to decide how much work they can finish. But how can they do that without talking about time? The effort to do something is not the same as the time it will take to finish it. This is especially true when planning an iteration with many people and tasks. It's clear now: Story Points don't work. What's the alternative? I'll let the people who manage projects for a living offer their alternatives, but I can tell you what I've done. As I got older and wiser, I stopped with the estimation charade altogether. I had my teams focus on short iterations with constant feedback from stakeholders. From the "scope, budget, and time" triangle, I always tried to keep two of them variable and fix the third one. If the customer was looking for a specific scope, we had a variable timeline and budget to finish it. We kept the scope and time flexible if the budget was non-negotiable. And if we had to deliver by a specific date, the scope and budget were on the table. Every company is different, and this doesn't work for everyone. But if it does, I hope you stop the charade. I'd love to hear about your experience estimating software. What crazy things does your company make you do?

'Nature is the reflection of the beautiful almighty' - Pranav Renaissance. 📍Dumboor #TripuraTourism #natureslove 📸Credit:- Krishna Kumar Rishi

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12 Design Patterns You Must Know 1. Factory Pattern 🏭 Imagine a factory that produces different products. Similarly, this pattern creates objects without specifying their exact class, making code flexible and easy to extend. 🧩 2. Observer Pattern 🔍 Like subscribing to updates! Objects (observers) register to watch changes in a subject. When the subject changes, observers are notified automatically. 📡🔔 3. Singleton Pattern 🕊️ The one and only! Ensures a class has only one instance globally accessible. Useful for managing shared resources like databases. 🌐🔒 4. Builder Pattern 🛠️ Building complex objects step by step. Think of it as assembling Lego bricks to create something intricate without the mess! 🧱🏗️ 5. Adapter Pattern 🌉 Bridging the gap! Converts the interface of one class into another interface clients expect. Makes incompatible components work together. 🔌🔌 6. Decorator Pattern 🎈 Like adding toppings to your pizza! Dynamically adds responsibilities to objects without changing their code. A flexible alternative to subclassing. 🍕✨ 7. Proxy Pattern 🕶️ Virtual representative! Controls access to an object, acting as a stand-in with additional functionality, like lazy loading. 🔒🔍 8. Strategy Pattern 🎯 Switching strategies seamlessly! Allows selecting algorithms during runtime. Useful when you want to provide multiple ways to accomplish a task. 🎮🔄 9. Command Pattern ⌨️ Encapsulates requests as objects, allowing parameterization of clients with different requests and queuing of requests. Think of it as a to-do list for your program. 📋📌 10. Template Pattern 📄 Standardized process steps! Defines the structure of an algorithm, letting subclasses override specific steps. Ideal for reusable workflows. 📊📈 11. Iterator Pattern 🔄 Tour guide for collections! Provides a way to access elements of a collection without exposing its underlying representation. 🚶‍♂️🗺️ 12. State Pattern 🚦 Like a traffic light! Allows an object to change its behavior when its internal state changes. Keeps your code organized as states pile up. 🚥🔄 #Coding #SoftwareEngineering #SoftwareDeveloper

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𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗥𝗘𝗦𝗧 𝗛𝗲𝗮𝗱𝗲𝗿𝘀 The Hypertext Transfer Protocol (HTTP) header is a component of HTTP and transmits extra data during HTTP requests and responses. The server uses the HTTP header and the browser to share metadata about the document and the data sent to the browser by the web server of the called website. A variety of data in the 𝗥𝗘𝗦𝗧 𝗵𝗲𝗮𝗱𝗲𝗿𝘀 can be used to trace down problems as they arise. As they show the meta-data related to the API request and response, HTTP Headers play a significant role in the API request and response. Headers contain data for: 𝟭. 𝗥𝗲𝗾𝘂𝗲𝘀𝘁 𝗮𝗻𝗱 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗕𝗼𝗱𝘆 𝟮. 𝗥𝗲𝗾𝘂𝗲𝘀𝘁 𝗔𝘂𝘁𝗵𝗼𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝟯. 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 𝟰. 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗖𝗼𝗼𝗸𝗶𝗲𝘀 Also, to the categories mentioned above, HTTP headers contain various information about different HTTP connection types, proxies, etc. The majority of these headers are used to maintain connections between clients, servers, and proxies. Thus, testing is not necessary. In general, we have 𝗿𝗲𝗾𝘂𝗲𝘀𝘁 𝗮𝗻𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗵𝗲𝗮𝗱𝗲𝗿𝘀. We set a request header when sending a request to an API and get some headers with a response. The common header structure is in the form 𝗡𝗮𝗺𝗲:𝘃𝗮𝗹𝘂𝗲, but it can have many values separated using a comma. Some 𝗰𝗼𝗺𝗺𝗼𝗻 𝗵𝗲𝗮𝗱𝗲𝗿𝘀 are: 🔹 𝗔𝘂𝘁𝗵𝗼𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻: which contains the client's authentication information for the requested resource. 🔹 𝗔𝗰𝗰𝗲𝗽𝘁-𝗖𝗵𝗮𝗿𝘀𝗲𝘁: This header instructs the server which character sets the client accepts and is set with the request. 🔹 𝗖𝗼𝗻𝘁𝗲𝗻𝘁-𝗧𝘆𝗽𝗲: Specifies the response's media type (text/html or text/JSON), which will aid the client in processing the response's body. 🔹 𝗖𝗮𝗰𝗵𝗲-𝗖𝗼𝗻𝘁𝗿𝗼𝗹: The client may keep and reuse a cached response for the duration specified by the Cache-Control header. This is the cache policy set by the server for this response. _______ If you like my posts, please follow me, @milan_milanovic, and hit the 🔔 on my profile to get a notification for all my new posts. Grow with me 🚀! #programming

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To start with Machine Learning: 1. Learn Python 2. Practice using Google Colab Take these 2 free courses: • Introduction to Python Programming (Udacity) • Machine Learning Crash Course (Google) If you need a bit more time before diving deeper, finish the following Kaggle tutorials: • Intro to Machine Learning • Intermediate Machine Learning At this point, you are ready to finish your first project: The Titanic Challenge on Kaggle. If Math is not your strong suit, don't worry. I don't recommend you spend too much time learning Math before writing code. Instead, learn the concepts on-demand: Find what you need when needed. From here, take the Machine Learning specialization in Coursera. It's more advanced, and it will stretch you out a bit. The top universities worldwide have published their Machine Learning and Deep Learning classes online. Here are some of them: • MIT 6.S191 Introduction to Deep Learning • DS-GA 1008 Deep Learning • UC Berkeley Full Stack Deep Learning • UC Berkeley CS 182 Deep Learning • Cornell Tech CS 5787 Applied Machine Learning Many different books will help you. The attached image will give you an idea of my favorite ones. Finally, keep these three ideas in mind: 1. Start by working on solved problems so you can find help whenever you get stuck. 2. ChatGPT will help you make progress. Use it to summarize complex concepts and generate questions you can answer to practice. 3. Find a community here on 𝕏 and share your work. Ask questions, and help others. During this time, you'll deal with a lot. Sometimes, you will feel it's impossible to keep up with everything happening, and you'll be right. Here are the good news: Most people understand a tiny fraction of the world of Machine Learning. You don't need more to build a fantastic career in the space. Focus on finding your path, and Write. More. Code. That's how you win.

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𝗗𝗼 𝗬𝗼𝘂 𝗡𝗲𝗲𝗱 𝗧𝗼 𝗞𝗻𝗼𝘄 𝗔𝗹𝗹 𝗗𝗲𝘀𝗶𝗴𝗻 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀? The answer is no. Even though we have 23 design patterns, around ten are mostly used in everyday development. Knowing which patterns exist overall is good, but you need to know these very well. Design patterns can be divided into three main types: 𝟭. 𝗖𝗿𝗲𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 These design patterns deal with object creation mechanisms, trying to create objects in a manner suitable to the situation. Important patterns in this group are: 🔹𝗙𝗮𝗰𝘁𝗼𝗿𝘆: This pattern allows delegating the instantiation logic to factory classes. The Factory Method creates objects without exposing the instantiation logic to the client. 🔹𝗦𝗶𝗻𝗴𝗹𝗲𝘁𝗼𝗻: The Singleton pattern ensures that a class has only one instance and provides a global point of access to it. It's useful when exactly one object is needed to coordinate actions across the system. 𝟮. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 These patterns deal with the composition of classes and objects which form larger structures. Important patterns in this group are: 🔹𝗔𝗱𝗮𝗽𝘁𝗲𝗿: This pattern works as a bridge between two incompatible interfaces. It wraps an existing class with a new interface to become compatible with the client's interface. 🔹𝗙𝗮𝗰𝗮𝗱𝗲: The Façade pattern provides a unified interface to a set of interfaces in a subsystem. Façade defines a higher-level interface that makes the subsystem easier to use. 🔹𝗗𝗲𝗰𝗼𝗿𝗮𝘁𝗼𝗿: This pattern dynamically adds/overrides behavior in an existing method of an object. This pattern provides a flexible alternative to subclassing for extending functionality. 🔹𝗣𝗿𝗼𝘅𝘆: The Proxy pattern provides a surrogate or placeholder for another object to control access to it. In its most general form, a proxy is a class functioning as an interface to something else. 𝟯. 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 These patterns are specifically concerned with communication between objects and how they interact and distribute work. Important patterns in this group are: 🔹𝗖𝗼𝗺𝗺𝗮𝗻𝗱: The Command pattern encapsulates a request as an object, thus allowing users to parameterize clients with queues, requests, and operations. 🔹𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲 𝗠𝗲𝘁𝗵𝗼𝗱: This pattern defines the program skeleton of an algorithm in a method called template method, which defers some steps to subclasses. 🔹𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: The Strategy pattern defines a family of algorithms, encapsulates each one, and makes them interchangeable. Strategy lets the algorithm vary independently from clients that use it. 🔹𝗢𝗯𝘀𝗲𝗿𝘃𝗲𝗿: This pattern defines a one-to-many dependency between objects so that all its dependents are notified and updated automatically when one object changes state. #technology #softwareengineering #programming #techworldwithmilan #developers

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#HappyUltoRathYatra May the divine Trinity bestow upon us peace, prosperity, and good fortune😌 #TripuraTourism #HappyBahudaYatra 🎥Credit: @xpulse_rider_roy (IG)

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