Data Augmentation is one of the most important yet underrated aspects of a machine learning system and has a significant impact on the model's performance. In this article, we will go over some prevalent image augmentation techniques and also discuss why such methods are required in the first place.
We will try to answer various questions such as: why are image augmentations necessary for any machine learning pipeline? What are the techniques used to achieve the objective? How can we use such techniques using python, OpenCV, and NumPy?
Why is it necessary?
First of all, we should ask ourselves whether data augmentation is worth…
Preprocessing raw images for machine learning pipelines
Almost all modern-day cameras capture raw format images and process them in a format commonly known as sRGB, suitable for humans to see. However, one might wonder what all the techniques are used to convert the raw images into sRGB format are? Why was it necessary? Also, one might wonder how to use raw images or process them in a certain manner to get better performance on some machine learning tasks. This article attempts to answer all such questions in addition to step-by-step python code for each process.
Most of the filters on social media apps such as Snapchat, Instagram…
A comprehensive list of resources to learn advanced mathematics for machine learning
Mathematics forms the basis of most of the machine learning algorithms. Therefore, it is imperative to have a good grasp of mathematics to understand machine learning. While most of the data scientists are aware of basic mathematical concepts such as Linear Algebra, Statistics, etc. but many of them are not aware of some deep mathematical concepts that can help them have a clearer understanding of how an algorithm works or allow them to understand the latest research in machine learning.
In this article, I have shared resources for advanced mathematics courses, which help machine learning. The topics discussed in this…
In this article, I have shared a 1-month plan to learn the basics of Natural Language Processing. Natural Language Processing is a vast subject and multidisciplinary subject that uses concepts from Computer Science, Linguistics, Neuroscience, etc. and is one of the most popular research area in Machine Learning. This one-month plan can be used to prepare for data science interviews or to start a project in NLP.
What should I know beforehand?
To properly understand the material for this week, the following material should be well understood or the material covered in the courses:
- Numpy
- Pandas
- Matplotlib
- Scikit-Learn
- Basic TensorFlow/PyTorch(not mandatory but recommended)
Let’s Go!
In last…
Machine Learning
How to improve the results obtained using Mean Squared Error Loss
Mean Squared Error is one of the most used and most straightforward regression-based loss function in Machine Learning and Data Science. It’s is used in a range of tasks such as Linear Regression on tabular data to specific use-cases in computer vision, NLP, Reinforcement Learning, etc. In addition to MSE, MAE is also widely used and is highly similar to MSE Loss.
Despite being highly used in Machine Learning, it has its share of flaws, which I would like to highlight in this article. There are specific ways to minimize its weaknesses to get better results, which are discussed at…
A 3-month plan to learn about the mathematics behind machine learning
In this article, I have shared a 3-month plan to learn mathematics for machine learning. As we know, almost all machine learning algorithms make use of concepts of Linear Algebra, Calculus, Probability & Statistics, etc. Some advanced algorithms and techniques also make use of subjects such as Measure Theory(a superset of probability theory), convex and non-convex optimization, and much more. To understand the machine learning algorithms and conduct research in machine learning and its related fields, the knowledge of mathematics becomes a requirement.
The plan that I have shared in this article can be used to prepare for data science…
My journey with interviewing for a Data Science Internship position with Microsoft
Microsoft was one of the software companies that hired interns at my university for the 2021 summers. This year, it was the first time that Microsoft offered any Data Science Internship for pre-final year undergraduate students.
Microsoft set the requirements as follows:-
- The student must have a minimum CGPA of 8.
- The student should be pursuing a Computer Science or Mathematics major.
All the eligible students had to fill the Internship application form on the Microsoft Career website with a resume. Students who had filled the application form received the test link within 1–2 days.
Online Test:
About 60–70 students give the…
Aryansh Omray
Computer Science Undergraduate, IIT(BHU), Varanasi https://www.linkedin.com/in/aryansh-omray/
