Hello there !! Hope you are doing well👋. My name is Pankaj Kumar Barman. I am very glad you are here.

  
   I have completed Post Graduate in M.Sc in CS and aspiring AI in healthcare Research, My Key interests are : Brain and AI, Computer Vision, Machine Learning 🏠   Living: Raiganj, India

Connect with me :

Technologies included to my day to day activity!! :

👨‍🏫 About Me :

• Career Goals : Becoming a successful AI Researcher. And the interest to rerearch and understand on the below fundamental questions--> 1) At what age during the human life span do different tissues with�in the brain stop ‘maturing’ and start ‘aging’? 2) Do different regions of the brain mature and age at different rates? 3) Are the last regions in the brain to mature among the first, or the last, to show signs of aging? • Working project experience : Brain and AI : Neuroimaging ,MRI Data, Brain Study through AI, Ageing . At what age during the human life span do different tissues with�in the brain stop ‘maturing’ and start ‘aging’? Do different regions of the brain mature and age at different rates? Are the last regions in the brain to mature among the first, or the last, to show signs of aging? Machine Learning based : Privacy-preserving support vector machine training blockchain-based encrypted IOT data in smart cities. NLP based : Patronizing and Condescending Language (PCL) detection in paragraphs extracted from news articles in english. Data Analytics based : 1. US Superstores data analysis. Technology used - Power BI, Excel , Python. 2. US Bank Customer segmentations . Technology used - Power BI , Excel, Python. 3. IPL data analysis . Technology used - Python , statistics , numpy seaborn , ML. In my free I love to play outdoor games like football, cricket and leasing some quality music and drawing. In the year 2019 I had participated in the Reliance Foundation Youth Sports (RFYS) football tournament which is held every year all over India and we were the only team who achieve the championship from Siliguri and promoted to play further matches in Kolkata. It was once in a life experience I had my college life. • Interested in AI Research and Explore and also very much interested in to Know how AI and ML can help future Space mission so efficiently . • Technologies worked with : Ms Excel, Power BI , MYSQL , SQLite , Python, Numpy, Pandas, Scikit-Learn , Machine Learning , Data Science , c++ , Advanced Python. • Soft Skills : Data storytelling, Data Visualizations, Business Strategy, Problem solving, Creative Thinking, Leadership, Relationship Building.

👨🏻‍🎓 Education

M.Sc. in Computer Science, Ramakrishna Mission Vidyamandira, Belur Math, Howrah, India.
Graduation in Computer applications MAKAUT
Siliguri, India.

Languages:

🇮🇳 Bangla : Native
🏴󠁧󠁢󠁥󠁮󠁧󠁿 English : Advanced
🇮🇳 Hindi : Intermediate

Sports / Game / Activities / Hobby :

🏏 Cricket, ⚽ Football, 🏸 Badminton, ♟️ Chess
🏊‍♂️ Swimming, 🏃‍♂️ Running, 🚶‍♂️ Walking
✈️ Travelling

My featured Respositories

RESUME

PANKAJ KUMAR BARMAN's Projects

-analyses-the-features-of-orthopedic-patients-and-making-a-decision-whether-a-patients-is-normal-or-

#Analyses the features of Orthopedic patients and making a decision whether a patients is Normal or Abnormal. Algorithms Used : K-NN Testing Score : 83% K-NN Training Score : 75% Naive Bayes Testing Score : 76% Naive Bayes Training Score : 78% Precision = TP / (TP + FP) Precision : 0.886 Recall = TP /(TP + FN) Recall : 0.8703 F1_score = 2*(Precision*Recall)/(Precision+Recall) F1_score : 0.8785 Key Activities : 1. Normalization 2. EDA 3. Classification_report 4. StandardScaler 5. Feature importance

573-pankaj

This is the Descriptions of my Data Journey !!

anisul-islam

This repository contains my GitHub profile and also a detailed portfolio.

apiforheroku

Deploying ML model API in Heroku

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

awesome-public-datasets

A topic-centric list of HQ open datasets.

check-whether-a-orthopedic-patients-is-normal-or-abnormalnot

KNN :K-nearest neighbors (KNN) algorithm is a type of supervised ML algorithm which can be used for both classification as well as regression predictive problems. However, it is mainly used for classification predictive problems in industry. The following two properties would define KNN well − Lazy learning algorithm − KNN is a lazy learning algorithm because it does not have a specialized training phase and uses all the data for training while classification. Non-parametric learning algorithm − KNN is also a non-parametric learning algorithm because it doesn’t assume anything about the underlying data