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Automatic Full Compilation of Julia Programs and ML Models to Cloud TPUs

Google's Cloud TPUs are a promising new hardware architecture for machine learning workloads. They have powered many of Google's milestone machine learning achievements in recent years. Google has now...

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Julia Programming Opportunities via IBKR Investors’ Marketplace

Julia programming language finds its applications in trading, financial data science algorithms and visually stunning plots. It often pairs up with technology built in C++ and R.

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Never miss an update from IBKR Quant Blog! Sign up for the newsletter and stay up-to-date on deep learning, artificial intelligence (AI), Blockchain, Python, R and Data Science as other transformative...

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Introduction to Julia – Part I

This article introduces the Julia programming language, which is specifically designed for scientific computing, that solves the “two-language problem”, i.e. it provides the performance at par with C...

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Introduction to Julia – Part II

Let’s get started with the installation. Here are the steps to install Julia.

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Introduction to Julia – Part III

Algorithmic trading is an example of a field that requires intensive computing capabilities in some cases. In such a field, processing data faster using an easy-to-write programming language can add a...

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Data Manipulation and Visualization Techniques in Julia – Part I

In this article, we’ll look at data manipulation and visualization techniques in Julia.

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Data Manipulation and Visualization Techniques in Julia – Part II

Basic arithmetic operations can be performed on individual columns.

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Data Manipulation and Visualization Techniques in Julia – Part III

The package RDatasets.jl in Julia helps you import all the in-build packages in R that can be used for testing purposes.

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The Brass Tacks of Julia Programming – Part I

Let’s do some basic arithmetic operations using Julia. There are multiple ways of performing the same operation.

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Introduction to Statistical Thinking – Part I

In this article, we’ll go step by step in deconstructing the decision-making process under limited information. We’ll look at some examples, the jargon and the importance of statistics in the process.

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The Brass Tacks of Julia Programming – Part II

A matrix is an array of numbers represented as a vector of vectors. Here’s how you can create a matrix.

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Data Manipulation and Visualization Techniques in Julia – Part IV

Julia has a “missing” object that is used for unavailable data. You can use skipmissing() function to perform operations ignoring the missing values.

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The Brass Tacks of Julia Programming – Part III

However, using 2 languages to perform a certain operation can be a challenge. Hence, Julia provides an option to use R and Python code by using the “PyCall” and “RCall” packages.

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Jupyter Notebook Shortcuts

Notebooks are tools that allow us to use markdown along with our code, to improve readability and really add to that storytelling aspect of a project.

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Top Skills to Prepare for a Quant Interview

With the ever-increasing demand for quantitative traders, it’s no surprise that more and more people are interested in this career path.

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How to Launch Your Career as a Risk Quant in 2024?

It is nearly impossible not to develop a strong skill set in programming languages like Python and R, as these are widely used for data analysis and modeling in finance.

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How to Get a Job at a Hedge Fund

Skills required at a hedge fund encompass a diverse set of abilities tailored to the demands of the financial industry and to provide you with career opportunities.

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