Deepak Mehra
Senior Software Engineer at Arcesium
Uttarakhand, India
Summary
👤
Senior🎓
Top SchoolDeepak Mehra is a Senior Software Engineer with seven years of industry experience, currently building solutions at Arcesium after progressing from software engineer to senior engineer there. He blends hands-on engineering with a background in management consulting at ZS, enabling him to translate complex business requirements into efficient technical implementations across fintech and pharma domains. Deepak has a strong foundation in computer science from DIT University and furthered his skills through targeted AI and privacy scholarships at Udacity. Known for improving business processes and delivery efficiency, he leverages both technical depth and domain context to drive measurable outcomes. Based in Uttarakhand, India, he brings a practical, product-oriented approach and an appetite for secure, privacy-minded AI work that isn’t obvious from title alone.
7 years of coding experience
4 years of employment as a software developer
Bachelor of Technology - BTech, Computer Science and Engineering., Bachelor of Technology - BTech, Computer Science and Engineering. at DIT UNIVERSITYSecure and Private AI Scholarship Challenge, Computer Science, Secure and Private AI Scholarship Challenge, Computer Science at UdacityKendriya Vidyalaya Sangathan
English, Hindi
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (42)
breast-cancer10
machine-learning-models10
random-forest-classifier10
machine-learning10
cancer-detection10
theory10
validation10
classifier10
svm-classifier10
image-data10
agriculture10
deep-learning10
leaf10
cross-validation10
neural-network10
Programming languages (5)
Github contributions (5)
mehra-deepak/Plant-Disease-Detection
Aug 2019 - May 2021
Plant Disease Detection is one of the mind-boggling issues when we talk about using Technology in Agriculture. Although researches have been done to detect whether a plant is healthy or diseased using Deep Learning and with the help of Neural Network, new techniques are still being discovered. For Fewer Data Classical Machine Learning Models are said to outstand given the data is pre-processed well. On the same theory here is my approach for Detecting whether a plant leaf is healthy or unhealthy by utilizing the classical Machine Learning Models, Pre-processing the Image Data. The data was fed to 7 Machine Learning Models with 10 fold cross-validation out of which Random Forest Classifier outperformed all the other models giving an accuracy of 97% on the test set.
Contributions:18 commits, 1 PR, 17 pushes in 1 year 8 months
classifiersaidleafmindimage-data
mehra-deepak/CN-DS-ALGO
Aug 2020 - Nov 2020
Contributions:131 pushes, 1 branch in 3 months
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