Senior Data Scientist at Grab | Freelance Data Scientist at GA | AI/ML PhD Scholar at NTU
class Prasanth(Human):
pronouns = ("He", "Him")
code = ["Python🐍", "R", "SQL", "HTML", "CSS", "Matlab", "LabView", "Go"]
ide = ("atom", "jupyter-notebook", "notepad++", "vscode", "Goland")
technologies = {
"data_science": {
"tools": ["tensorflow", "keras", "sklearn", "scipy", "nltk", "numpy", "pandas", "matplotlib",
"seaborn", "opencv", "GPT", ...],
"concepts": {
"Machine Learning": ['Linear & Logistic Regression', 'SVM', 'KNN', 'Decision Trees', 'Gradient Boosting', 'MLP', 'Ensemble', ...],
"Deep Learning": ['CNN', 'RNN', 'GPT'],
"Signal Processing": ['Spectral', 'FFT', 'Wavelets', 'STFT', 'Stockwell']
}
"systems": ["classification", "regression", "clustering", "recommendation", "object-recognition", "nlp"]
},
"expertise": ["Brain signals", "EEG", "Epilepsy", "Automated Detection", "MedTech", "Data Analytics",
"Dynamic Pricing", "Fraud Detection", "User Engagement", ...],
"web": {
"back_end": {
"python": ["flask", "django", "dash"],
},
}
"dev_ops": ["AWS", "Apache Spark", "Airflow"],
"databases": ["PostgreSQL", "MySql", "sqlite", "Datalake", "DataWarehouse"],
}
if __name__ == "__main__":
from time import sleep
from random import choice
from kitchen import yogurt, water, snacks
from fitness import hiit, strength_training, jogging, walking, hiking
import laptop
import work
prasanth = Prasanth()
while True:
sleep(8 * 60 * 60)
workload = work.get_daily_workload()
while len(workload) > 0:
choice(yogurt(prasanth), water(prasanth), snacks(prasanth), fruits(prasanth))
laptop.code(prasanth)
choice(hiit(prasanth), strength_training(prasanth), jogging(prasanth), walking(prasanth), hiking(prasanth)