Today almost all businesses are integrating AI in their systems to gain leverage and beating others to the market. The ones who adapt and adopt appropriately, seamlessly(automation) implementing and delivering solutions with minimal human intervention are establishing themselves in the market. Machine learning software systems that identify patterns in data...
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Why do we need causal inference when we have correlation?
In this post, I delineate a topic which is garnering attention, pretty quickly!, over the past years inspiring revolution about how we perceive AI. The idea of Causal Inference & its tools was propounded by Judea Pearl, who also espoused a probabilistic approach to AI. He describes causal inference as...
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Evolution of Recurrent Neural Networks.
In this post, I attempt to provide a concise history about Recurrent Neural Networks(RNN) & its advanced versions: why did they come into existence?
why did they become senile over time? what are the current generations of RNNs?
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Bayesian vs Frequentist ideology.
Bayesian: The rationale behind using a bayesian framework is not only the Bayes update rule or the availability of (subjective)prior if any exists, but is mainly due to marginalization and conditioning(of unknown on the known), which drive the modeling process in a Bayesian framework.
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Identifying endocrine cancer with AI.
Here I discuss my attempt at applying Computer vision & Deep learning techniques to detect endocrine & other colon related cancer: BE,suspicious, HGD, Cancer, polyp.
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