Neelabh Pant
Director Of Global AI at Cloudera
Texas, United States
Summary
👤
Senior🎓
Top SchoolNeelabh Pant is a Director of Global AI for Retail at Cloudera with a decade of experience applying ML and generative AI to real-world retail problems like real-time video analytics, personalized customer journeys, and in-store safety. He previously spent seven years at Walmart Global Tech advancing forecasting, legal document automation with LLMs, and multivariate time series solutions, rising to Senior Manager of Data Science. Holding an MS and Ph.D. in Computer Science (ML & AI) from UT Arlington, he blends academic rigor with hands-on model development and production deployment. He also contributes practical deep learning projects on GitHub—experimenting with Keras networks and ARIMA/SARIMA time series forecasting—showing a preference for both classical and deep approaches. Based in Texas, he focuses on translating cutting-edge research into measurable business impact across global retail operations.
10 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at The University of Texas at ArlingtonHigh School, High School/Secondary Diplomas and Certificates, High School, High School/Secondary Diplomas and Certificates at Aryaman Vikram Birla Institute of Learning.Bachelor of Engineering (B.Eng.), Computer Science, Bachelor of Engineering (B.Eng.), Computer Science at Birla Institute of Applied Sciences, Bhimtal
English, Hindi, Punjabi
Stackoverflow
807reputation
86kreached
0answers
7questions
Github Skills (18)
python10
pandas10
machine-learning10
keras10
time-series-forecasting10
neural-network10
scikit9
scikit-learn9
tensorflow9
forecasting6
deep-learning6
coefficients6
spatial-index6
dataframe6
grid-search6
Programming languages (1)
Github contributions (5)
neelabhpant/Deep-Learning-in-Python
May 2017 - Mar 2020
Hands-on, practical knowledge of how to use neural networks and deep learning with Keras 2.0
Role in this project:
Data Scientist
Data ScientistContributions:38 commits, 50 pushes, 1 branch in 2 years 10 months
Contributions summary:Neelabh's contributions focused on building and improving machine learning models using the Keras library within the context of the provided deep learning repository. They developed a one-layer neural network using Keras to solve a classification problem, specifically predicting the survival of passengers on the Titanic dataset. The user also refined this initial model, added a second layer, experimented with different model parameters, and compared the performance of multiple models, including those using Adam and SGD optimizers. Furthermore, the user also implemented time series forecasting models using ARIMA and SARIMA approaches.
hands-onknowledgedeep-learninghandsneural-networks
neelabhpant/Spatial_Data_Analysis
Apr 2017 - Sep 2017
Contributions:16 commits, 19 pushes, 1 branch in 4 months
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