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๐Ÿง‘โ€๐Ÿซ 59 Implementations/tutorials of deep learning papers with side-by-side notes ๐Ÿ“; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), ๐ŸŽฎ reinforcement learning (ppo, dqn), capsnet, distillation, ... ๐Ÿง 

Home Page: https://nn.labml.ai

License: MIT License

Python 45.00% Makefile 0.06% Jupyter Notebook 54.94%

annotated_deep_learning_paper_implementations's Introduction

ใ€Œ

Hello There
I'm CyberIngeniero, ML Engineer & AI Specialist.


~ Nibaldo ~

ใ€


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Hi ๐Ÿ‘‹, I'm Nibaldo

ML Engineer | Master in advanced & Applied IA | Master in Full Stack Web Development | MSc Statistics | Math Teacher

๐Ÿ‘จโ€๐Ÿ’ป About Me

#!/usr/bin/python
# -*- coding: utf-8 -*-

class DataScientist:
    def __init__(self):
        self.name = "Nibaldo Pino Araya"
        self.role = "Team Leader | ML Engineer | Statistician"
        self.current_work = "Leader of Modelling & Analytics Team."
        self.current_work_place = "HDI Seguros Chile"
        self.current_learning = ["Master in PMP"]
        self.personal_website = ""
        self.interests= ["ML","DL","IA","Statistics"]
        self.language_spoken = ["es_ES", "en_US"]

    def say_hi(self):
        print("Thanks for dropping by.")

me = DataScientist()
me.say_hi()

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