Problem Solver

Jibin Mathew

Jibin Mathew

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:

  1. Machine Learning
  2. Deep Learning
  3. Recurrent Neural networks
  4. Generative adversarial neural network
  5. Convolutional Neural Networks
  6. LSTM
  7. Dynamic Co-attention Networks
  8. Classification
  9. Regression
  10. Predictive Analysis
  11. Natural Language Processing/Understanding
  12. Chatbots
  13. Tensorflow
  14. Keras
  15. TFLearn
  16. EDA
  17. Neural Turing Machines
  18. Boltzmann Machine

Jibin Mathew's Problem Solving Experience:

  1. 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%
  2. 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%
  3. Built a solution for textiles to identify purity and composition of fabric using deep learning. accuracy of 94%
  4. Created a solution to identify human faces and their emotions with retail applications
  5. Created generative chatbots, which would learn from a dataset and generate responses
    to queries using a sequence to sequence model.
  6. Created a solution to create a Text summarization using Natural Language Processing and Deep Learning
  7. Created a sentiment analyzer using RNNs with an accuracy of 90%
  8. Created a Lead Generation tool to identify potential lead for an organization matching the vertical the organization wants to focus. accuracy - 98%