Areas Jibin Mathew is Knowledgeable in:
I am interested in Any associated with Artificial Intelligence, Machine Learning, Deep Learning, Chatbots, and Blockchain. I am good with cloud infrastructure.
Techniques Jibin Mathew Uses:
I use a combination of Machine Learning and Deep Learning to solve the problems associated with AI.
The language of choice is Python.
Deployment Infrastructure is AWS - GPU instances.
Jibin Mathew's Problem Solving Skills:
- Machine Learning
- Deep Learning
- Recurrent Neural networks
- Generative adversarial neural network
- Convolutional Neural Networks
- Dynamic Co-attention Networks
- Predictive Analysis
- Natural Language Processing/Understanding
- Neural Turing Machines
- Boltzmann Machine
Jibin Mathew's Problem Solving Experience:
- I created an award-winning Sales Intelligence Platform, which would identify potential customers and predict their buying power, identify right salesperson for your customer, Sales forecasting. accuracy - 91%
- Solution to classify e-commerce products into classes using Images and their descriptions, which used a combination of Convolutional Neural Networks and LSTMs. accuracy - 93%
- Built a solution for textiles to identify purity and composition of fabric using deep learning. accuracy of 94%
- Created a solution to identify human faces and their emotions with retail applications
- Created generative chatbots, which would learn from a dataset and generate responses
to queries using a sequence to sequence model.
- Created a solution to create a Text summarization using Natural Language Processing and Deep Learning
- Created a sentiment analyzer using RNNs with an accuracy of 90%
- Created a Lead Generation tool to identify potential lead for an organization matching the vertical the organization wants to focus. accuracy - 98%