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Rahul Bhadani
Pursuing Ph.D., Electrical Engineering | Intelligent Transportation & Quantum Science Researcher |
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Often while working with sensor data (or signal), we find that data are often not clean and exhibit a significant amount of noise. Such noise makes it harder to perform further mathematical operations such as differentiation, integration, convolution, etc. Further, such noise poses a great challenge if we are meant to use such signals for real-time operations such as controlling an autonomous vehicle, a robotic arm, or an industrial plant, as noise tends to amplify in any downstream mathematical operations.

In such a case, one generic approach is to smooth out the data to remove the noise. We seek smoothing…

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MAML is a class of meta-learning algorithms created by Stanford Research and UC Berkeley Alum Dr. Chelsea Finn. MAML was inspired by the idea behind the question that how much data is really needed to learn about something. Can we teach algorithms to learn how to learn?

In such a context, there are a few challenges with conventional machine learning algorithms:

  1. Intensive training is required
  2. Labeled data for some problems may be limited
  3. The performance of the network may be sensitive to the choice of hyperparameters

In such respect, meta-learning algorithms can be designed to address the following tasks:

  1. Dynamic…

Image by the author. Z = Y⁶— X⁶

It is always convoluted and challenging to install a CUDA toolkit and library that needs to interact with your NVIDIA GPU on an Ubuntu machine. However, if done right, the CUDA toolkit with your NVIDIA GPU can be a great tool that can harness the power of GPU to produce fast applications.

Basic Requirements

The basic requirement for following instructions in this article is a computer with Ubuntu 20.04 installed with an NVIDIA GPU. In my case, it was NVIDIA GeForce GTX 1650 Ti.

Further, at the time of writing this article, I installed the latest version of the CUDA toolkit which…

Data Science, Data Visualization, Statistics

Image generated by the author

Several engineering and science applications deal with timeseries data. For example, in the case of autonomous driving, several augmented and on-board sensors collect information about speed, acceleration, fuel usages, etc. in the form of timeseries data.

Usually, the same kind of information is gathered from multiple sensors that involve some kind of sensor fusion to build confidence around the gathered dataset. However, because of the inherent physics behind these sensors, there is always some kind of lag involved in data collected from various sensors.

Statistical sciences provide a rich set of tools for finding time-shift between two timeseries. For timeseries…

Image created by the author using a MATLAB script

In my previous article, I wrote about using PBS job schedulers for submitting jobs to High-Performance Clusters (HPC) to meet our computation need. However, not all HPC support PBS jobs. Recently my institution also decided to use another kind of job scheduler called Slurm for its newly installed clusters.

Taken from its documentation¹, Slurm is an open-source, fault-tolerant, and scalable cluster management and job scheduler Linux cluster. As a cluster workload manager, Slurm has three key functions:

  1. It allocates access to resources to users for some duration of time so they can execute their computational jobs.
  2. It provides a framework…

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High-Performance Clusters or HPC is an excellent platform to perform any optimization that requires a huge amount of RAM and takes hours or sometimes days to run. Usually, academic institutions and research institutions are equipped with HPC infrastructure. HPC is a high-performance computer with a huge amount of RAM and storage space for research tasks to meet computing needs.

Unlike a personal computer, HPC is used by several people on the university campus who log in to HPC via ssh remotely. HPC provides a job scheduling mechanism by which a user can submit their program to run. The requested program…

Image by the author

R Markdown is a powerful tool that lets you generate rich PDF using TeX engine. In R Markdown you can integrate prose and your analysis along with code, its outputs, and graphics. However, the use of R Markdown is not limited to the R language itself but a variety of other languages can be integrated.

When it comes to writing your code along with explanations and descriptions, R Markdown is very similar to Jupyter Notebook, but there are several things that R Markdown can do that Jupyter Notebook lacks. For example, with Jupyter Notebook, it is not straightforward to include…

Screenshots from the Apple Stocks app: Image by the Author

2020 saw the rise of new and young investors. To tap the sudden influx of new investment funds, several companies filed for IPO or went public through a special purpose acquisition company or SPAC also called a reverse merger. In total, they raised a whopping $24 billion as of December 2020 in the US Stock Market¹. Examples of companies merging with SPACs include electric vehicles (EV), cannabis, technology, gaming, and finance.

How to choose the right SPACs

Out of all SPACs in 2020, the most successful was Live Oak Acquisition Corp that provided a return of approximately 171% since its…

Graph of iShares Global Clean Energy ETF in 2020. Source: Google Finance

For decades, academics and researchers have been warning about the consequences of climate change. Deforestation, air pollution due to non-renewable energy sources, and industrialization have led to several irreversible changes. Greed has triumphed for short-term wealth and affluence over the human species' survival in the long run. Big oil companies such as Exxon Mobil, tobacco companies, asbestos, and lead industries even went to greater lengths to make sure that the public does not catch up with the sentiments of climate scientists, researchers, and pro-environment policy makers² ¹.

Even though there is no dispute among scientists³ about the impact of human…

The picture was taken by the author in Montreal, Canada in April 2019

Ever wondered how an urban fantasy looks like? Have you ever imagined a life out of the concrete roads, magnetic trains, skyscrapers, and piles of filth? Many of us have read about witchcraft, vampirism, supernatural creatures but they are mostly mythological, somewhat related to natural habitat, and far from being anthropogenetic.

Where a usual idea of fantasy stops, the idea of The City’s Son begins. Rail-wraith, electric damsels, shape-shifting creatures purely made up of garbage, and villains who are purely cranes and bulldozers, together they give rise to urban fantasy. You may think I am talking about the Transformers book…

Rahul Bhadani

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