AI Trends
Reporting, analysis and features from AIM's AI Trends section.
Top Books For Machine Learning Engineers (Recommended By Experts)
Ram Sagar ·
8 Outstanding Papers At ICLR 2021
The papers were evaluated for both technical quality and the potential to create a practical impact.
Srishti Deoras ·
Pinterest Open-Sources Big Data Analytics Tool Querybook: Major Features & Set Up Instructions
Querybook’s core focus is to make composing queries, creating analyses, and collaborating with others as simple as possible.
Ambika Choudhury ·
Guide to XLNet for Language Understanding
XLnet is an extension of the Transformer-XL model. It learns bidirectional contexts using an autoregressive method. Let’s first understand the shortcomings of the BERT model so that we can better understand the XLNet Architecture. Let’s se…
Pavan Kandru ·
All The Machine Learning Features Announced At Microsoft Ignite 2021
Ambika Choudhury ·
When Transformers Fail
Ambika Choudhury ·
Guide to ODE2VAE For Long-Term Motion Prediction
ODE2VAE, a representation learning model, achieves state-of-the-art performance in long-term motion prediction and imputation tasks
Rajkumar Lakshmanamoorthy ·
Hands-on TransUNet: Transformers For Medical Image Segmentation
TransUNet, a Transformers-based U-Net framework, achieves state-of-the-art performance in medical image segmentation applications
Rajkumar Lakshmanamoorthy ·
Reinventing Deep Learning Operation Via Einops
Aishwarya Verma ·
Top 8 AI Labs In India
Sejuti Das ·
Top AI Communities On Discord That every Data Scientist Should Join
With themes like weekly discussions on the latest news and releases in AI, this server is an excellent resource for enthusiasts wanting to learn.
Avi Gopani ·
10 Research Papers On Federated Learning
Federated learning was first introduced by Google in 2016
Amit Naik ·
Why Data Scaling is important in Machine Learning & How to effectively do it
Scaling the target value is a good idea in regression modelling; scaling of the data makes it easy for a model to learn and understand the problem.
Yugesh Verma ·
Understanding T-Test and P-Value Interpretation Using Python
The T-test is a hypothesis testing method that helps in testing the significance of two or more groups and determining the important differences between the groups being compared. It is a variation of inferential statistics and is mostly u…
Victor Dey ·
Top Resources To Learn About Federated Learning
Simply put, federated learning is the decentralised form of ML. Today we list resources to help you kickstart your journey with federated learning.
Debolina Biswas ·
Understanding Direct Domain Adaptation in Deep Learning
To fill the gap between Source data (train data) and Target data (Test data) a concept called domain adaptation is used. It is the ability to apply an algorithm that is trained on one or more source domains to a different target domain.
Vijaysinh Lendave ·
Difference Between LSTM Vs GRU in Recurrent Neural Network
Long Short Term Memory in short LSTM is a special kind of RNN capable of learning long term sequences. They were introduced by Schmidhuber and Hochreiter in 1997. It is explicitly designed to avoid long term dependency problems. Rememberin…
Vijaysinh Lendave ·
How to Visualize a Random Forest with Fitted Parameters?
the decision tree was an example of a black-box algorithm in any random forest, that we can access to know how it works.by visualizing trees in random forest we can know about the model
Yugesh Verma ·
Why Are Indian Institutes Racing To Launch B Tech in AI Courses
Only 3 percent possess skills that are needed for jobs in emerging tech such as AI, machine learning, etc.
Amit Naik ·
5 Ransomware Attacks of 2021 That Blew The Internet
In June 2021, SonicWall recorded an all-time high of 78.4 million ransomware attacks across the globally.
Debolina Biswas ·