Important Machine Learning and Deep Learning Papers in 2021
Machine Learning suddenly became one of the most critical domains of Computer Science and just about anything related to Artificial Intelligence.
Every company is applying Machine Learning and developing products that take advantage of this domain to solve their problems more efficiently.
Every year, 1000s of research papers related to Machine Learning are published in popular publications like NeurIPS, ICML, ICLR, ACL, and MLDS.
The criteria are using citation counts from three academic sources: scholar.google.com; academic.microsoft.com; and semanticscholar.org.
“Key research papers in natural language processing, conversational AI, computer vision, reinforcement learning…
An exclusive invite-only app that is emerging amid a pandemic. Can you get an invite?
Bye, Instagram! Farewell, Spotify. See you later, Snapchat!
Why is this happening you might ask. Everyone is desperate to invite this exclusive audio-only social media platform packed with celebrities, talent shows, and excellent thought-provoking conversation. As stereotypical it might sound, it is called ‘Clubhouse.’
You might’ve heard of Clubhouse by now. It’s unlikely you’ve joined Clubhouse.
Clubhouse is an audio-based social media app. The company describes itself as
“New type of social product based on the voice that allows people everywhere to talk, tell stories…
Machine Learning suddenly became one of the most critical domains of Computer Science and just about anything related to Artificial Intelligence. Every company is applying Machine Learning and developing products that take advantage of this domain to solve their problems more efficiently.
“Key research papers in natural language processing, conversational AI, computer vision, reinforcement learning, and AI ethics are published yearly”
The area of Machine Learning has far-reaching applications from the text, audio, image, video to supervised and reinforcement learning. In this article, I have listed three novel Machine Learning articles that made a breakthrough in this field.
Neural networks are formed in three layers which are described below:
Passive layers that relays the same information from a single node to multiple outputs. This is the first point of entry for the Neural Network.
Performs mathematical computations on the inputs and produce a net input which is then applied with activation functions to produce the output. Usually, this layer is treated as a black box and much smaller than other layers.
Coalesces and concretely produces the output result from the complex computations from the previous layers.
Most neural network is formed in three layers, as stated above. Let’s…
Let me start by showing some of my details to establish trust to fellow readers:
There is secretly a complex relationship between our brain, body and sleeping pattern. How well you sleep at night can significantly change your well being and mood in the long run. The term “sleep” simply means the body’s rest cycle — the natural, shut-eye process easily reversible periodic state of many living things that are marked by the absence of wakefulness and by the loss of consciousness of one’s surrounding.
When you are asleep, science explains that sleep is triggered by a complex group of hormones that are active in the brain, and that respond to cues from the body…
In the past years, Data Science has transformed its way into all parts of society from travel, banking, entertainment, etc. Data Science delivers robust and actionable insights from the intelligently mined data to add value to the particular environment it is being applied.
“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” — Geoffrey Moore
However, there are challenging issues that fellow Data Scientist has to face — from understanding complex algorithms, processing tons of data to managing and delivering expectations in a business environment. …
Machine learning (ML) is a method of data analysis that automates analytical model building. It is a branch of technology that allows computer systems to learn from vast amounts of data, identify patterns within images and text and make statistical decisions with minimal human intervention.
At its most basic, Machine Learning uses pre-programmed algorithms that receive and analyze input data to predict output values within an acceptable range. As new data is fed to these algorithms, they learn and optimize their operations to improve performance, developing ‘intelligence’ over time.
Choosing the right Machine Learning algorithm depends on several factors such…
Techopedia describes algorithm as:
In its purest sense, an algorithm is a mathematical process to solve a problem using a finite number of steps. In the world of computers, an algorithm is the set of instructions that defines not just what needs to be done but how to do it.
Still don't understand? Think of it something like this: An algorithm is essentially a recipe for a cake. There are many ways to bake a cake, but by following a recipe, a person knows when to first preheat the oven, then measure out the flour, add butter, flavouring and so…
According to Kiplinger, Robo-adviser firms have seen 3 times the digit growth from 2012 to 2019 and Cerulli associated reported robo investment has $60 billion in assets and could quickly amass up to 385 billion in the next 5 years. This is truly outstanding.
During the 2008 financial crisis, investors were burnt by considerable losses in the stock market, pushing them to put their wealth into passive investment vehicles that generate returns with the least amount of work. …
Machine Learning Engineer | Data Enthusiast | Learner