A person perceives 90% of information through sight. Clear visualization makes it easier to convey complex information. And what could be more confusing and more complicated than the stock and securities market?

Trading platforms, market forecasting agencies create tons of web-based tools for traders and analysts to interact with datasets. Technical progress is their unconditional assistant. Financial data can be visualized in various ways depending on the purpose. Let’s look at the outstanding JavaScript tools in data visualization capabilities.

1️⃣ Highcharts

DEEP LEARNING

The tool is based on the PyTorch deep learning framework. The task of data compression is to minimize the size of the data and at the same time preserve information as much as possible.

More about the library

Currently, CompressAI provides:

• Custom operations, layers, and neural network models for data compression;
• Part of the functionality from the official TensorFlow library for compression;
• Pretrained end-to-end compression models for image compression tasks;
• Scripts for evaluating and comparing trained models with classical methods of compressing photo and video data

The current version of the library does not support multi-GPU training. …

DATA SCIENCE

Python and R have long been the standard for Data Science. The essence of their opposition is that both languages ​​are great for working with statistics. While Python has clear syntax and a large number of libraries, the R language was developed specifically for the statistician, and therefore is equipped with high-quality data visualization. SQL stands out — because if the data is already in tables, then it’s more luck than a reason for frustration — and Scala — mainly due to the fact that the most popular distributed data processing framework Spark is written in it.

To conduct primary data analysis and decide on the future of a feature, SQL and the command line alone are enough because data science is, first of all, not about libraries with catchy names but an approach. Nevertheless, such minimalism has its limits (and a beginner may generally be scared off), and at some point, you will still have to turn to more advanced research tools. …

DEEP LEARNING

Researchers at Binghampton University and Intel Corporation have developed a model that recognizes deepfakes by predicting heartbeats. The classifier uses photoplethysmogram data to recognize fake videos. An important assumption in the model is that it learns to recognize deepfakes that have been generated using a set of publicly available architectures. This imposes restrictions on the use of the model in real applications.

The approach detects fake videos with an accuracy of 97.27% and a generative model of deepfakes with an accuracy of 93.39%.

DeepFakes problem

The popularity of deepfakes has grown in recent years. Artificially generated videos of famous people are used for a variety of purposes, from filters on social media images to political propaganda and false news. …

DEEP LEARNING

FrankMocap is a new state-of-the-art neural network for 3D body and hand movement recognition that was recently developed and published by researchers at Facebook Artificial Intelligence Research (FAIR).

DEEP LEARNING

Objectron is a new SOTA dataset, recently presented by Google AI, which intended to improve 3D object recognition in videos. The dataset contains 15 thousand short video clips, each containing annotation of 3D boundaries of objects. The dataset contains both real clips and synthetic ones, that is, generated based on real ones.

What is the problem

The dataset is designed to facilitate the process of training models for 3D objects on 2D image and video data.

While 2D prediction only provides 2D bounding boxes, by extending prediction to 3D, one can capture an object’s size, position, and orientation in the world, leading to a variety of applications in robotics, self-driving vehicles, image retrieval, and augmented reality. …

PRODUCTIVITY

Do you do all the things time-management gurus tell you to but still end up less productive than you thought you would? There are several secrets that not everyone will tell you about. I will touch on 4 of the ones that stood out to me.

After an immense amount of research on the world’s most productive people, it becomes evident that they define productivity differently. It’s not about doing more, not about stuffing your schedule to the brim, not about getting more things done. …

PROGRAMMING

When you are just starting to learn Python, someone may explain to you that you can add your source folder to the PYTHONPATH environment variable, and then your code can be imported from other directories. Very often, the explainer forgets to say that, in most cases, this is a bad idea.

Some people find this on the Internet; others know it from their own experience. But too many people (especially inexperienced programmers) think that there are no other alternatives.

Even if you know there is an alternative; it is not always easy to get used to and start using it. Python tools are confusing because there is a lot of software built on top of one another, with a ton of overlap and problems that come with it. …