“Tanoy is a highly skilled analytics professional who exhibits great attitude and keenness to ideate and deliver on best in class analytics solutions to address the business challenges. Challeging status quo and thinking out of the box is an expectation with him.”
About
Tanoy spends most of his time researching, exploring and experimenting about the world of…
Contributions
Activity
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Determination Of Capital Adequacy Ratio And Risk Weighted Assets In Banks : Basel III Regulatory Capital Framework Basel III regulatory capital…
Determination Of Capital Adequacy Ratio And Risk Weighted Assets In Banks : Basel III Regulatory Capital Framework Basel III regulatory capital…
Liked by Tanoy Dewanjee
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Capital Adequacy Ratio Vs Leverage Ratio In The Banking Sector Capital Adequacy Ratio (CAR) is the ratio of a bank’s capital in relation to its risk…
Capital Adequacy Ratio Vs Leverage Ratio In The Banking Sector Capital Adequacy Ratio (CAR) is the ratio of a bank’s capital in relation to its risk…
Liked by Tanoy Dewanjee
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India has: Largest # of developers in the world Largest # of silicon designers in the world Largest amount of data in the world Largest IT services…
India has: Largest # of developers in the world Largest # of silicon designers in the world Largest amount of data in the world Largest IT services…
Liked by Tanoy Dewanjee
Experience & Education
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Descipr
View Tanoy’s full experience
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Licenses & Certifications
Courses
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Basics Of Financial Markets
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Projects
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DNN Speech Recognizer
Built a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline. The completed pipeline will accept raw audio as input and return a predicted transcription of the spoken language. Overall pipeline is summarised as below :
1. This is a pre-processing step that converts raw audio to one of two feature representations(Spectrograms, Mel-Frequency Cepstral Coefficients (MFCCs)) that are commonly used for ASR.
2. Here, an acoustic model is…Built a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline. The completed pipeline will accept raw audio as input and return a predicted transcription of the spoken language. Overall pipeline is summarised as below :
1. This is a pre-processing step that converts raw audio to one of two feature representations(Spectrograms, Mel-Frequency Cepstral Coefficients (MFCCs)) that are commonly used for ASR.
2. Here, an acoustic model is built which accepts audio features as input and returns a probability distribution over all potential transcriptions.
3. in the pipeline takes the output from the acoustic model and returns a predicted transcription. -
Estimation of turbulent effect of jet injection in a subsonic and supersonic flow
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Estimated the turbulent effect of jet injection at different angle in a subsonic and supersonic flow of fluids using Numerical analysis method.
Developed comparative analysis of velocity, pressure and turbulent kinetic energy distribution along the flow.
Used fluent, Mat Lab, Ms-excel and PowerPoint for the aforesaid project.
Honors & Awards
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DataQuest 2023 - People Choice Award
HSBC
My team has been recognised for proposing a proactive payments fraud detection framework using generative ai capabilities which aims at creating synthetic fraud samples and explore and introduce embedded context in the transaction activity to proactively protect customers from payments fraud.
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Data Quest 2022 - Category Runners Up
HSBC
My team have been recognised as runners up in the “Energise for Growth” category for proximity based business development tool we developed for Wholesale banking relationship managers. This tool helps RMs to spot the new to bank prospects within close vicinity of their existing customer base and complement the leads with all required demographics, filmographies, financial and risk information and finally uses internal data to find out any existing relationships with our book of customers. It…
My team have been recognised as runners up in the “Energise for Growth” category for proximity based business development tool we developed for Wholesale banking relationship managers. This tool helps RMs to spot the new to bank prospects within close vicinity of their existing customer base and complement the leads with all required demographics, filmographies, financial and risk information and finally uses internal data to find out any existing relationships with our book of customers. It has drastically reduced the effort required for lead prospect research by proving useful and timely insights and helped them focus more on business development.
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Runner up - Client Network Banking Hackathon
HSBC
Proposed a detailed solution to identify key new to bank customers using our existing client network across the globe.
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Leading Light Award
HSBC
In recognition to the exceptional performance in spearheading the team in service delivery
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Team Star Award
HSBC
In recognition of great performance and exhibiting impressive skills
Languages
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English
Professional working proficiency
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Hindi
Native or bilingual proficiency
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Bengali
Native or bilingual proficiency
Recommendations received
2 people have recommended Tanoy
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Here is my version to import MSFT graphrag into Neo4j, mostly copied from Michael, but changed some minor details :) https://lnkd.in/eAkksaX5
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Using percentages is not always correct… Today I was reading a small news, and one line caught up my eye quickly. The original line is - Among the…
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Meet your member of parliament Mr AI… Al Steve, an Al candidate in the 2024 UK general election, contested in Brighton Pavilion has secured 179…
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After 4 months of hard work, we finished our 𝗟𝗟𝗠 𝗳𝗿𝗲𝗲 𝗰𝗼𝘂𝗿𝘀𝗲, which teaches you an end-to-end framework for prod LLM & RAG systems…
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Bad News: Koo is shutting down. Worst News: People blaming founders, bad management, VCs, excessive funding, etc., for this shutdown and listing…
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