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Aditya Chatterjee

Aditya Chatterjee

Aditya Chatterjee is an Independent Algorithmic Researcher, Software Developer and Technical Author. He is the founding member of OPENGENUS, an organization with focus on changing Internet consumption

Higashikurume, Tokyo, Japan •
35 posts •
Algorithms

Algorithm to check if a linked list is sorted

In this article, we have explored an algorithm to check if a given Linked List is sorted or not in linear time O(N). It takes constant space O(1).

Shubham Kumar
Algorithms

Check if Linked List is Empty

Checking if the given Linked List is empty depends on the ways Linked List has been formed (with or without root). We have covered both approaches.

Aayushi Rawat
Data Structures

Probabilistic Data Structures

This is a general overview of probabilistic data structures (with examples of data structures over 5 different categories).

Ethan Z. Booker
Software Engineering

Tough Interview questions on C Programming

These are some of the most tough Interview questions on C Programming which tests your knowledge on how well you know the language. Even if you are not a master of C, you must try it once.

Aditya Chatterjee Aditya Chatterjee

Contribute and grow 🌱 with Hacktoberfest 2020

Hacktoberfest is a month long virtual event where you can make four contributions towards your favorite Open Source project (such as Cosmos by OpenGenus). You will not only get to learn new things but also get free goodies delivered to you at your doorstep.

Ue Kiao, PhD Ue Kiao, PhD
Data Structures

List of Advanced Data Structures

This article has the list of 100+ Advanced Data Structures that you must understand to prepare to solve advanced problems and compete in competitions like ICPC, Google Code Jam, Facebook Hacker Cup and many more.

Aditya Chatterjee Aditya Chatterjee
Machine Learning (ML)

Capsule neural networks or CapsNet

Capsule neural networks or CapsNet is an artificial neural network which consists of capsules(bunch of neurons) which allow us to confirm if entities(components) are present in the image. We will cover Capsule Networks in depth.

Sandeep Bhuiya
Data Structures

Must read research papers on Data Structures

We presented research papers on Data Structures that are a must read for everyone. These come from authors like Raimund Seidel, Knuth, Rubinchik and others

OpenGenus Foundation OpenGenus Foundation
Algorithms

Must read research papers on Algorithms

We presented some of the must read research papers in the field of Algorithms. The papers come from authors like C. A. R. Hoare, D. E. Knuth, V. Strassen and many others.

OpenGenus Foundation OpenGenus Foundation
Algorithms

Bozosort

Bozosort is a random sorting algorithms where the key idea is to swap any two elements of the list randomly and check if the list is sorted. The average time complexity of Bozosort is O(N!) and the space complexity is O(1).

OpenGenus Foundation OpenGenus Foundation

Best Programming Memes of 2019

This is the ultimate list of the best programming memes of 2019. It includes epic memes of Elon Musk, Greta Thunberg to attacking JavaScript. Enjoy.

OpenGenus Foundation OpenGenus Foundation
Algorithms

Easiest IMO problems that will make you feel like a Genius

IMO problems are known to be difficult but we have identified 5 problems which you can solve without using a paper. This will make you feel like a GENIUS

OpenGenus Foundation OpenGenus Foundation
Machine Learning (ML)

Understand basic TensorFlow programming concepts

We understand basic TensorFlow programming concepts using a code to add two numbers in TensorFlow. We created placeholders like tf.placeholder, operations like tf.constant and tf.add, sessions using tf.session and configuration using tf.configProto

Aditya Chatterjee Aditya Chatterjee
Machine Learning (ML)

Training vs Inference

Training and Inference are two major processes of Machine Learning and is deeply connected. Training is the process by which we generate various parameters such as weights and biases which are used in a particular model. Inference is the process of using the trained model to do a particular task

Aditya Chatterjee Aditya Chatterjee
Machine Learning (ML)

Deep Learning on 2-Dimensional Images

Applying deep learning concepts on images has proved to be one of the important work which has resulted in early detection of diseases resulting in saving millions of life to monitoring activities on the entire Earth We take a look at medical images, Satellite Images and the various Python libraries

Priyanshu Shekhar Sinha Priyanshu Shekhar Sinha
Machine Learning (ML)

Deep Learning for Medical Imaging and Diagnosis

One of the major medical challenges that we face today is the early detection of diseases so that the proper threatment can be applied. This can be solved by applying machine learning to analyse MRI scan, CT Scan, Xray Scans, InfraRed Images, Arthoscopy, UV radiation, Scintigraphy and Ultrasound

Priyanshu Shekhar Sinha Priyanshu Shekhar Sinha
Machine Learning (ML)

Evolution of CNN Architectures: LeNet, AlexNet, ZFNet, GoogleNet, VGG and ResNet

It all started with LeNet in 1998 and eventually, after nearly 15 years, lead to ground breaking models winning the ImageNet Large Scale Visual Recognition Challenge which includes AlexNet in 2012, ZFNet in 2013, GoogleNet in 2014, VGG in 2014, ResNet in 2015 to ensemble of previous models in 2016.

Aditya Chatterjee Aditya Chatterjee
Machine Learning (ML)

BLAS vs BLIS

BLAS (Basic Linear Algebra Subprograms) and BLIS (BLAS Like Interface Software) are libraries that have revolutionized scientific computing by accelerating execution of mathematical operations on a vast range of platforms. In short, BLIS is the new generation alternative to BLAS

Aditya Chatterjee Aditya Chatterjee
Machine Learning (ML)

Types of Neural Network optimizations

The types of neural network optimizations are weight pruning, structured pruning, convolution, fully-connected, structured group, structure ranking with activations like Lp norm, block pruning, model thinning, compression schedule, regularization, group lasso, group variance, quantization and others

OpenGenus Foundation OpenGenus Foundation
similarity measurement

Minkowski distance

Minkowski distance is a distance/ similarity measurement between two points in the normed vector space (N dimensional real space) and is a generalization of the Euclidean distance and the Manhattan distance. See the applications of Minkowshi distance and its visualization using an unit circle.

OpenGenus Foundation OpenGenus Foundation
similarity measurement

Damerau Levenshtein distance

Damerau Levenshtein distance is a variant of Levenshtein distance which is a type of Edit distance. Damerau stated that the four operations in Damerau Levenshtein distance correspond to more than 80% of all human misspellings. It adds an extra operation named transposition to its set of operations

OpenGenus Foundation OpenGenus Foundation
similarity measurement

Levenshtein distance

evenshtein distance is a type of Edit distance which is a large class of distance metric of measuring the dissimilarity between two strings by computing a minimum number of operations (from a set of operations) used to convert one string to another string. It is a way of pairwise string alignment.

OpenGenus Foundation OpenGenus Foundation
Machine Learning (ML)

Build / Install Eigen Library from source

In this article, we explore the way to build and install Eigen library from source using cmake. Eigen is an efficient open-source C++ library for linear algebra, matrix and vector operations, geometrical transformations, numerical solvers and related algorithms.

OpenGenus Foundation OpenGenus Foundation
similarity measurement

Edit distance

Edit distance is a large class of distance metric of measuring the dissimilarity between two strings by computing a minimum number of operations (from a set of operations) used to convert one string to another string. It can be seen as a way of pairwise string alignment.

OpenGenus Foundation OpenGenus Foundation
similarity measurement

Euclidean vs Manhattan vs Chebyshev Distance

Euclidean distance, Manhattan distance and Chebyshev distance are all distance metrics which compute a number based on two data points. All the three metrics are useful in various use cases and differ in some important aspects such as computation and real life usage.

OpenGenus Foundation OpenGenus Foundation
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