RESEARCH & IP

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

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

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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.

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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

02
Jun
Natural Language Processing with BERT

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops Last Saturday, AI Researcher Indrajit Singh presented a marvellous workshop on “Bidirectional Encoder Representations from Transformers” – also called “BERT” in short. We are in the era of Pre-trained models in AI. The figure below shows tons of pre-trained models which have taken root. BERT is one of the core models […]

Posted in: Natural Language Processing,
Tags: ALBERT, BERT, ELMO, GLoVe, GPT, Named Entity Recognition, natural language generation, natural language processing, NER, Next sentence prediction, NLG, NLP, NLP with DL, OpenAI, transformers, word embedding,
28
May
Introduction to Graph Neural Networks

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops Recently, our AI Researcher Gouthaman Asokan presented a superb session on introduction to Graph Neural Networks (GNNs). Structured vs Unstructured Data :- Images and text are structured data. Convolutional Networks, Recurrent Neural Networks, Autoencoders work well on the structured data as they can be converted to the matrix or vector like format. […]

Posted in: Graph Neural Networks, Pharma,
Tags: DiGraphs, Drug Interactions, GCN, GNNs, Graph Convolutional Network, graph neural networks, GraphNet, Graphs, Knowledge Graphs, Multigraph, node classification, social network analysis, unstructured data,
19
May
Transformers for NLP

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops Last Saturday, our AI Lab Researcher Indrajit Singh presented an exhaustive webinar on Transformers, which are used in NLP. Introduction To combine the advantages from both CNNs and RNNs, [Vaswani et al., 2017] designed a novel architecture using the attention mechanism. This architecture, which is called as Transformer, achieves parallelization by […]

Posted in: Natural Language Processing,
Tags: AddNorm, deep learning, encoder-decoder, Multi-head attention, MXNet, natural language processing, NLP, position-wise FFN, positional encoding, Residual block, self-attention, seq2seq, Sequence-to-sequence, skip connection, tensorflow, transformer, transformerdecoder, transformerencoder,

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