I'm going to start this post off by talking about Lua. I promise it will make sense. This post is made by and made for someone who enjoys using Python for their projects, and it employs a Python-based evaluation of the languages mentioned.

In this article, I will explain what ISAs are, why they are profitable, and how to open them for those residing in the UK looking for easy and tax-free investment opportunities.

Ever felt frustrated when a chatbot loses context after you explore a side topic? Current LLM (Large Language Model) conversation models are limited by their linear structure, which hinders context preservation and flexibility in branching and merging conversations. To overcome this, I propose a graph-managed LLM conversation approach, allowing for broader discussions with specific side topics while maintaining the full context.

First, a short introduction. Most people know Vercel as a front-end solution, however Vercel introduced many new features recently that make it a powerful tool for running small webapps for free. If you know what vercel is and why you want to deploy your project to vercel, skip here.

Vercel is a platform that enables developers to build, deploy, and manage modern web applications. Having tested it myself, I can vouch for the fact that once integrated, it is quite simple to use. With Vercel, developers can simply push their changes to their GitHub repository, and the platform will automatically redeploy the site and update the server with the new code (CI/CD Anyone?). The platform also provides a dashboard for each site, offering insights into status, recent deploys, and domain information.

I have been working as a Software Engineer at Amazon Prime Video in London since May 2022. Job search in the UK as a Turkish citizen can be a quite difficult process, and not many people have visibility into how it works. This document aims to provide context and help to get you started from someone who has been through the process.

Immutability is a concept in computer science and programming that refers to the property of an object or data structure being unable to be modified or changed after it is created. In immutable systems, once an object is created, its state cannot be altered. Instead, if a change is needed, a new object or data structure is typically created with the desired changes, leaving the original object unchanged. Immutability is often valued for its benefits in maintaining data integrity, simplifying code, and enhancing concurrency in multi-threaded applications. Immutable objects are commonly used in functional programming and in scenarios where predictability and consistency are crucial.

Introducing Emoji.dutl.uk: A Simple Website that Serves Emojis as Images

Emojis have become a part of our daily communication on social media, messaging apps, and other digital platforms. However, quite often when you need the emoji in image format, it is not a very trivial task. That's why I have created Emoji.dutl.uk.

As the creator of Emoji.dutl.uk, I wanted a simple solution to serve emojis as images on my websites. I found it tedious to create an image file for each emoji, so I created this website to solve that problem. It's a static website that serves emojis as .png files, making it easy to use them as favicons.

This article assumes you have basic programming skills and an engineering/programming background.

(Copied over from the SimplyMarkdown repository. This website is entriely composed with SimplyMarkdown as well.)

Welcome to SimplyMarkdown, the simplest framework for creating websites from your Markdown files! With SimplyMarkdown, you can easily and quickly turn your directory of Markdown files into a stunning website without having to deal with any complicated configurations or bloated features.

As a solo developer who enjoys creating fun and easy-to-use tools in my free time, I wanted to make something that was both lightweight and effective. And that's exactly what SimplyMarkdown is all about! It's a simple and straightforward framework that lets you focus on your content, not the technical details.

Coursemaker is program to parse sentences in a corpus, and sort them in an order ideal for vocabulary study. See github repo for the complete source code.

Most used 100 words in a language make up approximately 50% of words in a corpus (This of course varies from language to language. E.g. it is lover in agglutinative languages). If you sort the most used words and start learning words from this list (frequency sorted list fsl) you can effectively increase your hit rate in the corpus.

typ-o is a simple js-based web application that allows you to type in the standard Russian Cyrillic input method, while highlighting the keys you press.

I wrote it on a Thursday night after I couldn't find one that highlighted the pressed keys and was frustrated.

I plan to implement a simple game-based practice mode too, that's future work. (done!) Check typ-o out!

UPDATE: I made typ-v, which has a game mode. It does not have a virtual keyboard support (I found it quite limiting, and hard to make cross-platform compatible.)

People started wearing masks in Istanbul during the coronavirus outbreak. After I realized this, I wanted to know what percentage of people were wearing masks and since I had all the time in the world due to schools getting cancelled, I took on this personal project.

I used OpenCV to detect people in a video stream provided by İBB (the metropolitan municipality of Istanbul). I saved the people detected in the last minute and when new detections arrived, I compared them with the saved images to avoid duplicates.

In this project, we implemented SketchyGAN, an image-to-image GAN model that allowed for non-pixel-to-pixel transformations which was novel at the time. We followed the SketchyGAN paper and implemented the model in Keras instead of TensorFlow as the paper did.

Read about our project from inzva:

Having graduated from the “junior position” they were assigned to in the previous batch of AI Projects, undergraduates from Boğaziçi University, Cemre Efe Karakaş and Eylül Yalçınkaya, along with another undergraduate from Istanbul Technical University, Burak Bekçi, a previous participant in our Applied AI Study Group, had one of the most acclaimed presentations in AI Projects history as they showcased a very fun way to implement GANs by turning their faces into sketches.

The purpose of this project was to convert a sketch image into an actual image. A GAN architecture is used since this is an image-to-image translation problem. The team first wanted to replicate the results of their reference paper, SketchyGAN [1]. This special GAN architecture contains the masked residual unit (MRU) as a novel component. Apart from the traditional convolutions and the features obtained from them, MRU layer takes downsampled and upsampled versions of the actual images as input during the encoding and decoding part in the generator. Apart from this novel architecture, SketchyGAN also use extra loss terms added to the original GAN loss, such as perceptual loss and diversity loss. The team showed their results by also presenting their own sketches translated into actual images.

https://inzva.com/reports/2019/ai-projects-3

• See our presentation for more details.
• See our GitHub repo for the implementation.

How did North Korea's economy, once better than the South, end up where it is today? A review of the economic plummet of one of the most closed modern societies and what led to it.

Author's Note:

One should be extremely wary of political agendas and propaganda while consuming any articles, pieces of news, or media about the handful of leftist governments in our world.

In this project, we aimed to explore the feasibility of using trigger word detection models to predict earthquakes. We were fortunate to have the guidance and expertise of a senior engineer from Is Bankasi, who provided valuable insights and guidance throughout the project. This project was part of Inzva's Applied AI Projects, which aims to give hands-on experience to aspiring data scientists and machine learning engineers.

To accomplish our goal, we used Andrew Ng's trigger word detection model, which is a widely used approach in the field of natural language processing. We adapted this model to listen to audio recordings of seismic activity continuously and output a higher value when the waveform suggests that the last waves might have been formed by the trigger word. Our hypothesis was that the preceding waves in the recording could provide information about the time to failure, allowing us to predict an earthquake.

We were excited to participate in a Kaggle competition where we applied our model to predict the timing of earthquakes based on seismic activity. The competition was a challenge, as we were working with a large dataset of around 610 million points, making data processing and training time-consuming. Despite these challenges, our team was able to place in the top 11% of participants, which was a great achievement for our first deep learning project.