#introduction to object oriented programming

Not everyone is the same, and everyone is different when it comes to their familiarity with how to do things.

Here's AAGD’s quick and easy algorithm to decide what you should use to build your game idea if you’re just starting out:

Do I know how to program? Do words like "object oriented” and “virtual function” have specific meaning to me? Unity, Unreal

Do I have some coding knowledge already? - Dragon Age Toolset, Skyrim Creation Kit, Source SDK

Am I starting on game development with no background whatsoever? Gamemaker, RPG Maker, Construct

I want to make an MMO! Stop. Make something simpler.

If you want to learn to code, it depends a lot on how self-driven you are. If you have trouble motivating yourself to do things, a local community college course for introduction to programming is probably your best bet. For those who are able to self-motivate and have little to no programming background, I suggest starting with C# and learning to use Unity alongside it. Microsoft has a great [C# learning resource] that has lessons and will walk learners through getting started and what the language is, and it uses Unity in its examples. If you want to learn C++, which is the language du jour of most game development (even Unity is really C++ under the hood), then I suggest working your way through the lessons at [LearnCPP].

[Join us on Discord] and/or [Support us on Patreon]

Got a burning question you want answered?

Short questions: Ask a Game Dev on Twitter

Short questions: Ask a Game Dev on BlueSky

Long questions: Ask a Game Dev on Tumblr

there's a few programming where i understand learning it to be able to develop and modify new things, but i dont understand why someone would make a new project with it. thats Java and Lua to me and new programs are made with both all the damn time.

Introduction

Artificial Intelligence (AI) and Machine Learning (ML) are transforming industries, from healthcare to finance. However, for beginners, the sheer volume of libraries, algorithms, and mathematical concepts can be overwhelming. How do you go from zero knowledge to building complex neural networks?

This AI/ML roadmap provides a structured path to help you navigate this exciting field, ensuring you build a strong foundation before tackling advanced topics.

Phase 1: The Foundations

Before diving into algorithms, you must master the tools of the trade. Skipping this step is the most common mistake aspiring data scientists make.

Mathematics for ML

You don't need a PhD in math, but you do need a solid grasp of core concepts:

Linear Algebra: Understanding vectors and matrices is crucial for data manipulation.

Calculus: Derivatives and gradients are the backbone of optimization algorithms.

Statistics & Probability: Essential for understanding data distributions and model evaluation.

Programming Skills

Python is the undisputed king of AI programming. Focus on:

Basic syntax and data structures (lists, dictionaries).

Object-Oriented Programming (OOP).

Environment management (Anaconda, Virtualenv, Jupyter Notebooks).

Phase 2: Data Analysis and Manipulation

Data is the fuel for machine learning. You must learn how to clean, visualize, and manipulate data effectively.

NumPy: For high-performance numerical computing.

Pandas: For data manipulation and analysis (DataFrames).

Matplotlib & Seaborn: For data visualization to uncover patterns and insights.

Phase 3: Core Machine Learning

Once you can handle data, it is time to learn the classic algorithms. This involves using Scikit-Learn, the industry-standard library for traditional ML.

Supervised Learning

Learning with labeled data:

Linear & Logistic Regression.

Decision Trees and Random Forests.

Support Vector Machines (SVM).

Unsupervised Learning

Finding hidden patterns in unlabeled data:

K-Means Clustering.

Principal Component Analysis (PCA) for dimensionality reduction.

Phase 4: Deep Learning and Neural Networks

This is where "AI" truly shines. Deep Learning mimics the human brain using neural networks. To master this, you will need to learn frameworks like TensorFlow or PyTorch.

ANN (Artificial Neural Networks): The basis of deep learning.

CNN (Convolutional Neural Networks): Used for image recognition and computer vision.

RNN (Recurrent Neural Networks) & Transformers: The standard for Natural Language Processing (NLP) and Large Language Models (LLMs).

Structuring Your Learning Path

Self-study is possible, but the landscape changes rapidly. Many learners find that a structured curriculum accelerates their progress significantly by filtering out noise and focusing on industry-relevant skills.

If you are looking for a comprehensive, mentor-led approach to cover everything mentioned in this roadmap, consider enrolling in a professional program. The AI & ML Training Certification offers a rigorous curriculum designed to take you from fundamentals to advanced deployment, ensuring you are job-ready.

Phase 5: Deployment and MLOps

Building a model is only half the battle; deploying it is the other. To become a full-stack ML engineer, you need to understand:

Model Deployment: Using Flask, FastAPI, or Streamlit.

Cloud Platforms: AWS, Google Cloud, or Azure AI services.

MLOps: Managing the lifecycle of ML models (versioning, monitoring).

Conclusion

Whether you’ve just received a long list of textbooks you need for a specific uni class or are looking for a particular book/research paper for a high school project, books (and journal subscriptions) can be expensive.

The good news is that there are plenty of resources online where you can find free PDF versions of most written materials, starting with Atkinson & Hilgard’s Introduction to Psychology and ending with Shakespeare’s Macbeth.

Note that although some of the websites below provide access to copyright-free texts only, or texts that publishers/authors have agreed to share freely, others have been accused of internet privacy.

However, many people see open access practices as morally acceptable, especially considering the unsustainable prices of academic textbooks and papers.

To quote a recent paper on the topic:

"Since shadow libraries are a product of the cooperation between scholars, who contribute texts and other resources (such as donations, volunteer work, etc.), shadow libraries represent a ‘bottom-up’, radical approach to open access: a physical approximation of the Platonic ideal of knowledge sharing that would exist if there were no legal, economic, or institutional barriers to the circulation of scholarly knowledge."

Free Textbooks

Library Genesis

Library Genesis, or Libgen for short, is a shadow online library website where college students can find academic books (including those that are hard to find/very expensive) and scholarly journal articles.

The site also hosts general-interest books, audiobooks, comics, magazines, and images.

Z-Library

Z-Library is another shadow library website that hosts college textbooks, scholarly journal articles, and general-interest books. It calls itself “the world’s largest e-book library.” It mirrors Library Genesis.

The front page also features some of the most popular books at the time. When we viewed it, these included “Thinking Fast and Slow” by Daniel Kahneman, The Book Thief by Markus Zusak, and Harry Potter the Complete Collection by J. K. Rowling.

You can also use the right-hand navigation menu to see the books that have been added most recently, as well as sort through books based on category.

Use the Book Request option if you can’t find a book you’re looking for. There’s no guarantee your book will be added, but community members look at requests to see what books to upload (you can also upload books).

PDF Drive

PDF Drive is an online library with a ton of free ebooks and PDF textbooks in various categories, including academic & education (but also lifestyle, personal growth, art, linguistics, etc.)

ForCoder.su

Forcoder.su has lots of online textbooks on programming. It also provides free access to online courses, like Apache Kafka for beginners and object-oriented programming with Python. Currently, there are hundreds of free courses available.

Online Mathematics Textbooks

Online Mathematics Textbooks is your source for free digital textbooks on all things math. It’s just one page featuring 77 textbooks.

Tech Books for Free Download

Tech Books for Free Download is where you’ll find free science and engineering books on topics ranging from data mining to general relativity.

There’s no way to search for books easily. However, the site is divided into books on Linux, Java, Microsoft, C and C++, Perl/Python, Science, Networking, Database, Security, and Assembly.

Free Tech Books

Free Tech Books is an open textbook library. It provides access to free computer science books and textbooks, plus lecture notes. All the books and lecture notes listed on this site are freely available on authors’ and/or publishers’ sites.

You can browse books by category (computer science, mathematics, supporting fields, operating system, programming/scripting, miscellaneous), author, publisher, or license.

Directory of Open Access Books

Directory of Open Access Books (DOAB) is a website that indexes and provides access to academic, peer-reviewed open-access books. All disciplines are covered, but there’s a particular emphasis on humanities, social sciences, and law.

Ubiquity Press

Ubiquity Press has been an open-access publisher of academic, peer-reviewed books and journals since 2012. It was founded by University of College London (UCL) researchers.

Research Papers

Sci-Hub

Sci-hub has the most expansive collection of research papers. Its mission is to “remove all barriers in the way of science.”

Directory of Open Access Journals

Directory of Open Access Journals (DOAJ) is an online directory of open-access, peer-reviewed research journals covering humanities, social sciences, technology, science, medicine, and art.

The directory indexes journals from different countries and languages. DOAJ is supported financially by publishers, libraries, and other organizations.

Wiley Open Access

Wiley Open Access provides peer-reviewed open-access journals across topics like biochemistry, economics, sociology, mathematics, and law.

SpringerOpen

SpringerOpen publishes open-access journals across a wide range of areas, mainly STEM.

Elsevier

Elsevier publishes open-access, peer-reviewed journals. You can search for journals by title, keyword, or subject (dentistry, nursing, decision sciences, etc.)

Springer Link

Springer Link provides access to ebooks, peer-reviewed journal articles, and other resources (mostly scientific).

BASE

BASE is a search engine for academic texts, including journals, digital collections, institutional repositories, etc. You can access about 60% of the indexed texts for free.

Study Guides

Bibliomania

Bibliomania has study guides to the most-read books, like “A Hero of Our Time,” “Animal Farm,” and even Irish politics. It also has over 2,000 classic texts, book summaries, author biographies, and more.

Books

Open Library

Open Library is an open library catalog of more than 3 million new and old books. The project was created by the nonprofit organization Internet Archive. It has also received partial funding from Kahle/Austin Foundation and the California State Library.

You can read old books without an account. However, for new books, you’ll need to set one up (it takes just a few minutes).

Internet Archive

Internet Archive is a digital library of ebooks. It also has free movies, music, and software.

Project Gutenberg

Project Gutenberg is a famous site where you can find lots of free books. There are more than 60,000 books in its collection.

Standard Ebooks

Standard Ebooks take public domain texts and make them as nice as new books. They fix typographical errors and typos, create cool cover art, and format the text for e-readers like Kindle and iPad.

Planet eBook

Planet eBook is where you can download free PDF copies of classics like Franz Kafka’s The Metamorphosis, Fyodor Dostoyevsky’s Crime and Punishment, and Joseph Conrad’s Heart of Darkness.

What really makes Planet eBook stand out is its UX. It’s one of those rare sites that are super easy to navigate and actually look good (aesthetically speaking).

The Ultimate Book Search Engine

The Ultimate Book Search Engine is an ebook search engine that includes 350 open directory sites that relate to ebooks. It was created by the Reddit user u/NotoriousYEG.

Classic Bookshelf

The Classic Bookshelf is a site where you’ll find lots of classic novels, everything from Charles Dickens and Leo Tolstoy.

Literature.org

Literature.org features classic works of English literature, both fiction and non-fiction.

Bartleby

Bartleby is a site that features both fiction and nonfiction books.

Fiction.us

Fiction.us has a ton of books, including fiction, short stories, children's picture books, poetry, books on writing, and plays.

Classic Literature Library

As the name suggests, Classic Literature Library is where you’ll find classic literature works.

Ideology.us

Ideology.us is a site that has ebooks on philosophy, psychology, sociology, politics, and education.

The Complete Works of William Shakespeare

The Complete Works of William Shakespeare is where you’ll find all of Shakespeare’s work. The site is run by The Tech, the largest and oldest newspaper by the Massachusetts Institute of Technology in Cambridge.

Read Books Online

Read Books Online has around 6,000 ebooks, including novels, short stories, poems, essays, plays, and non-fiction.

Public Bookshelf

Public Bookshelf is a site dedicated to romance novels.

Categories of ebooks here include contemporary romance, romantic suspense, historical romance, regency romance, inspirational romance, vampire romance, western romance, general romance, and fantasy and paranormal romance.

The Perseus Project

The Perseus Project is a digital library created by Tufts University with books from Ancient Rome and Greece, published in original languages and English.

Chest of Books

Chest of Books has books on a ton of different subjects, including animals, finance, real estate, science, and travel.

The Literature Network

The Literature Network has books by authors like Anne Bronte, Lewis Carroll, and Lord George Gordon Byron. It also features forums, literature summaries, and quizzes.

The Online Books Page

The Online Books Page is a site by the University of Pennsylvania that houses books in categories like philosophy, history, medicine, science, agriculture, music, anthropology, and more. The site also links to the following:

Banned Books Online: A directory of books that were once banned and links to places where you can read them in full.

A Celebration of Women Writers: A directory that lists online editions of literary works by women as well as resources about women writers.

Prize Winners Online: A directory of prize-winning books.

Many Books

Many Books is “your friendly neighborhood library.” It houses over 50,000 books in genres like romance, mystery, young adult, horror, and non-fiction. You can read books online or download them to your device.

Authorama

Authorama turns public domain books on sites like Google Books and Project Gutenberg into HTML format, making it easier to read them.

Audiobooks

Librivox

(29/03/2023)

Hello, how are you everyone?

Yesterday I started the 4th I studied about the random module but I had an anxiety attack and I didn't finish. (I'm better)

Today I finished the random and we started the array. But there's still a little bit left to finish. And during the afternoon I had several ideas of things I want to learn and I had a slight outbreak because there are so many things and how to organize myself.

But something I want to share is that I don't feel like I learn from Professor Angela, her teaching is not bad and she gives a lot of exercises.

BUT my head feels that something is missing and I know that I don't really think with it, precisely because the answers are easily accessible, which makes it easier to procrastinate or, in a slight error, look for the answer (no, I don't want moralistic advice on how this is wrong, I have a conscience, I'm just sharing my logic)

And why doesn't it seem to me that I'm learning algorithms and data structure, even though today, for example, I've seen array.

So, accessing the free university on github (I'll make a post, but I'll leave a link here too) I found the Brazilian version and saw a course on Introduction to Computer Science with Python and I loved it, because then I feel like I'm going to algorithms and data structure, and it's taught by the best college in my country (my dream included)

And then for me to stop feeling like a fraud and REALLY try hard.

I decided to make my own roadmap (not the official version yet) It will basically be:

Introduction to computer science part 1 and 2

Exercises from the algorithm course in python (I did it last year, but I really want to do it and make an effort this year)

Graphs

Data structure

Object orientation

programming paradigms

Git and GitHub

Clean Code

Design system

Solid

And only after that go back to 100 days (but now managing to do algorithm exercises for example) So then it would be:

100 days of code

django

Apis

Database

Practice projects.

Another thing I wanted to share (but I'll probably talk more about it in another post) is how the pressure/hurry of wanting to get a job is screwing up my studies.

I WILL NOT be able to learn things effectively on the run.

So I talked to myself and decided that this year I'm going to focus on learning as best I can, but without rushing to get a job (I have the privilege of living with my mother and she supports me) and then next year I'll go back to the call center to pay my bills and then look for a job in the area

I want to feel confident in my code, I want to REALLY know what to do and do it well.

But it won't be in a hurry, so I prefer peace to be able to learn in the best way and everything I want than to freak out and not leave the place.

Hi! I figured I'd make an introduction post for me to pin (since that's what everyone else is doing apparently) so here's everything you need to know about me:

If there's anything I missed or you want to know, feel free to ask me about it! I'm completely fine with getting random asks.

Introduction: 

In today's competitive market, creating high-quality Android applications requires adherence to best development practices.  Android app development agencies in Vadodara (Gujarat, India) like Nivida Web Solutions Pvt. Ltd., play a crucial role in delivering exceptional applications.  This article presents the 20 best Android development practices to follow in 2023, ensuring the success of your app development projects.

1.     Define Clear Objectives:

Begin by defining clear objectives for your Android app development project.  Identify the target audience, the app's purpose, and the specific goals you aim to achieve.  This clarity will guide the development process and result in a more focused and effective application.

 2. Embrace the Material Design Guidelines:

Google's Material Design guidelines provide a comprehensive set of principles and guidelines for designing visually appealing and intuitive Android applications.  Adhering to these guidelines ensures consistency, enhances usability, and delivers an optimal user experience.

 3. Optimize App Performance:

Performance optimization is crucial for user satisfaction.  Focus on optimizing app loading times, minimizing network requests, and implementing efficient caching mechanisms.  Profiling tools like Android Profiler can help identify performance bottlenecks and improve overall app responsiveness.

 4. Follow a Modular Approach:

Adopting a modular approach allows for easier maintenance, scalability, and code reusability.  Breaking down your app into smaller, manageable modules promotes faster development, reduces dependencies, and enhances collaboration among developers.

 5. Implement Responsive UI Designs:

Designing a responsive user interface (UI) ensures that your app adapts seamlessly to various screen sizes and orientations.  Utilize Android’s resources, such as ConstraintLayout, to create dynamic and adaptive UIs that provide a consistent experience across different devices.

 6. Prioritize Security:

Android app security is of paramount importance.  Employ secure coding practices, authenticate user inputs, encrypt sensitive data, and regularly update libraries and dependencies to protect your app against vulnerabilities and potential attacks.

 7. Opt for Kotlin as the Preferred Language:

Kotlin has gained immense popularity among Android developers due to its conciseness, null safety, and enhanced interoperability with existing Java code.  Embrace Kotlin as the primary programming language for your Android app development projects to leverage its modern features and developer-friendly syntax.

 8. Conduct Thorough Testing:

Testing is crucial to ensure the reliability and stability of your Android applications.  Employ a combination of unit testing, integration testing, and automated UI testing using frameworks like Espresso to catch bugs early and deliver a robust app to your users.

 9. Optimize Battery Consumption:

Battery life is a significant concern for Android users.  Optimize your app's battery consumption by minimizing background processes, reducing network requests, and implementing efficient power management techniques.  Android's Battery Optimization APIs can help streamline power usage.

 10. Implement Continuous Integration and Delivery (CI/CD):

Adopting CI/CD practices facilitates frequent code integration, automated testing, and seamless deployment. Tools like Jenkins and Bitrise enable developers to automate build processes, run tests, and deploy app updates efficiently, resulting in faster time-to-market and improved quality.

 11. Leverage Cloud Technologies:

Integrating cloud technologies, such as cloud storage and backend services, can enhance your app's scalability, performance, and reliability.  Services like Firebase offer powerful tools for authentication, database management, push notifications, and analytics.

 12. Ensure Accessibility:

Make your Android app accessible to users with disabilities by adhering to accessibility guidelines.  Provide alternative text for images, support screen readers, and use colour contrast appropriately to ensure inclusivity and a positive user experience for all users.

 13. Optimize App Size:

Large app sizes can deter users from downloading and installing your application.  Optimize your app's size by eliminating unused resources, compressing images, and utilizing Android App Bundles to deliver optimized APKs based on device configurations.

 14. Implement Offline Support:

Provide offline capabilities in your app to ensure users can access essential features and content even when offline.  Implement local caching, synchronize data in the background, and notify users of limited or no connectivity to deliver a seamless user experience.

 15. Implement Analytics and Crash Reporting:

Integrate analytics and crash reporting tools, such as Google Analytics and Firebase Crashlytics, to gain insights into user behaviour, identify areas for improvement, and address crashes promptly. This data-driven approach helps in refining your app's performance and user engagement.

 16. Keep Up with Android OS Updates:

Stay up to date with the latest Android OS updates, new APIs, and platform features.  Regularly update your app to leverage new functionalities, enhance performance, and ensure compatibility with newer devices.

 17. Provide Localized Versions:

Cater to a global audience by providing localized versions of your app.  Translate your app's content, user interface, and notifications into different languages to expand your user base and increase user engagement.

 18. Ensure App Store Optimization (ASO):

Optimize your app's visibility and discoverability in the Google Play Store by utilizing appropriate keywords, engaging app descriptions, compelling screenshots, and positive user reviews.  ASO techniques can significantly impact your app's download and conversion rates.

 19. Follow Privacy Regulations and Guidelines:

Adhere to privacy regulations, such as GDPR and CCPA, and ensure transparent data handling practices within your app. Obtain user consent for data collection, storage, and usage, and provide clear privacy policies to establish trust with your users.

 20. Regularly Update and Maintain Your App:

Continuously monitor user feedback, track app performance metrics, and release regular updates to address bugs, introduce new features, and enhance user experience.  Regular maintenance ensures that your app remains relevant, competitive, and secure.

 Conclusion:

What do I mean? Well let’s back up a little here.

Pokémon was created to simulate irl bug hunting/collecting in game format. The franchise was based off of something fun and engaging for small children and that’s part of it’s charm and why it got so popular.

Digimon on the other hand, was the solution to the girlish Tamagotchi toys. The company needed a brand that would attract a younger male audience, and also serve as a counterpart to the Tamagotchi toy line. 

While both spawned animes respectively, Digimon lagged behind Pokémon by a little more than a year, but Digimon’s concept was based on marketing and selling a virtual pet. (Something not unique to the 90′s time period). While Pokemon was focused more on the gameplay mechanics and subsequent character designs that they could market down the road.

The thing about Pokémon is that the franchise itself is fictional, and much more fantasy oriented than realistic. Digimon’s franchise is based off an object that exists in the real world but is connected to a fictional ‘programmed’ world that is dynamic and constantly changing on a whim. 

Only the very core mechanics of the Digimon games stay the same, but each entry into the franchise brings something fresh to the table; new characters, new game mechanics, and most importantly new virtual pet toys. This means fresh material can be added to the old, but can be unique enough to remain separate in style (kind of like fashion). If a season didn’t do too well, then they can scrap that and introduce something different. No two toys or games are alike. Each entry is unique.

This is not to say Pokémon doesn’t add new content to their franchise, it’s just less separate? Like, barring Mega Evolution or Z-Moves and the introduction of the fairy type, most of the gameplay is exactly the same as the last Pokémon game. Which some people like, but after a while can feel kinda stale. (Like eating nothing but pizza for a month. That gets kinda old really fast even if you like pizza.)

Sure, they crank out recolors new Pokémon each game, but it doesn’t really bring many new things to the table. (There’s also Rangers, PMD, and PL:A I know, but they’re not really the mainstream games and don’t come out annually enough to act like series additions to the franchise and also don’t have animes revolved around them).

And the animes? Well, both Digimon and Pokemon might have episodic seasons and some movies, but Digimon tends to hone in on stylizing their characters and giving them growth and development. It’s hard to make a show where the main character never ages, but it’s a whole lot more fun to show off a world where computer programs talk to each other and are influenced by humans both intentionally and unintentionally, which in turn affects the human world.