RESEARCH & IP

CellStrat is India’s top research firm in emerging areas of Artificial Intelligence, Machine Learning, Deep Learning and other cutting-edge technologies.

CONSULTING

CellStrat AI practice defines the standards in Artificial Intelligence design and consulting. Our Deep Learning algorithms are disrupting the way how business gets done !

EVENTS

Attend Disrupt4.0 events which drive the discussions around AI innovation and applications of Deep Learning in a variety of verticals. Register for the upcoming Disrupt events.

TRAINING & CERTIFICATION

Data Science and Artificial Intelligence are the hottest careers today ! Get certified with our industry-leading training courses and see your career take-off !

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Solutions Consulting in AI and Machine Learning

EraStrat defines the standard in AI and ML application design and development.

Backed by our market-leading research content, we have expertise in algorithmic design related to machine learning protocols, deep neural networks and training AI routines. We are expert in developing scalable machine learning programs and applications.

Contact us for all your ML design and development needs.

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RECENT POSTS

25
Jun
Explainable AI with Grad-CAM

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops Recently, our AI Lab Researcher Bismillah Kani presented a superb session on Grad-CAM, which is used to detect “why they predict what they predict“. In other words, it explains the AI algorithms, specifically, it explains the results of vision applications. Introduction :- Deep Learning in Computer Vision has achieved breakthrough performance […]

Posted in: Computer Vision, COVID-19,
23
Jun
Relational GCN for Heterogeneous Graphs

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops Recently, our AI Lab Researcher Gouthaman Asokan presented an amazing session on Relational Graphical Convolutional Networks (Relational GCN). These are particularly useful for mining heterogeneous groups. Table of Contents :- GCN HOMOGENEOUS AND HETEROGENEOUS GRAPHS KEY IDEAS OF RELATIONAL GCN FINDING PAGERANK USING MESSAGE PASSING BUILDING A RELATIONAL GCN FOR THE […]

Posted in: Graph Neural Networks, Publishing, Retail,
Tags: ACM Citation, Entity classification, GCN, GNN, graph analysis, Graph Convolutional Network, graph network, graph neural networks, graph theory, heterogenous graphs, homogeneous graphs, knowledge graph, Link Prediction, Message Passing, ontology, ontology graph, PageRank, pytorch, R-GCN, recommender systems, relational GCN,
17
Jun
Multi Agent Reinforcement Learning

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars I presented a session on Multi-Agent RL recently at the CellStrat AI Lab. Introduction :- In the normal Reinforcement Learning setup, you have one agent which interacts with the environment. It uses the Observation from the environment, performs actions and observes the rewards. In real life, many applications will involve several agents […]

Posted in: Reinforcement Learning,
Tags: Actor Critic, DDPG, Deep Deterministic Policy Gradients, MADDPG, Markov Games, Multi Agent Actor Critic, Multi Agent DDPG, Multi Agent RL, Policy Ensembles, policy gradients, Policy Inference, reinforcement learning, Unity ML,

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