Ryota Kawamura

Ryota Kawamura

@Ryota-Kawamura

川村亮太

Foxconn Japan
353
Followers
2
Following
14
Public Repos
0
Private Repos

Language Breakdown

Lines of code distribution across 13 owned repositories

169.3M Total LOC
Jupyter Notebook
154,967,282 lines
91.5%
N/A
Python
12,594,500 lines
7.4%
N/A
HTML
1,135,410 lines
0.7%
N/A
C#
340,101 lines
0.2%
N/A
Shell
215,211 lines
0.1%
N/A
Other
61,163 lines
0.0%
N/A
I

I-Shaped Developer

I-shaped

Specialist — deep expertise in Jupyter Notebook

Jupyter Notebook
Python
HTML
C#
Shell

Collaboration Network

Global Impact visualization

LIVE
Ryota Kawamura
0 active collaborators

Repos

14

PRs

0

Growth

+18%

Top Collaborators

No collaborator data yet.

Coding Streak

Contribution activity over the past year

1 day
9
Contributions
0
Commits
0
Pull Requests
Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun
Mo
We
Fr
Based on GitHub activity
Less
More

Top Repositories

Mathematics-for-Machine-Learning-and-Data-Science-Specialization

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

843 343
Jupyter Notebook
Generative-AI-with-LLMs

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

626 442
Jupyter Notebook
LangChain-for-LLM-Application-Development

In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.

211 153
Jupyter Notebook
How-Diffusion-Models-Work

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

175 94
Jupyter Notebook
Building-Systems-with-the-ChatGPT-API

In Building Systems With The ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model.

60 56
Jupyter Notebook
Generative-AI-for-Everyone

You’ll get insights into what generative AI can do, its potential, and its limitations. You’ll delve into real-world applications and learn common use cases.

49 22
Jupyter Notebook
LangChain-Chat-with-Your-Data

Start building practical applications that allow you to interact with data using LangChain and LLMs.

43 44
Jupyter Notebook
ChatGPT-Prompt-Engineering-for-Developers

In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications.

25 23
Jupyter Notebook
AI-for-Good-Specialization

Learn AI's role in addressing complex challenges. Build skills combining human and machine intelligence for positive real-world impact using AI

20 22
Jupyter Notebook
Functions-Tools-and-Agents-with-LangChain

You’ll explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.

16 20
Jupyter Notebook

Open Source Impact

Contributions to external projects

0 merged PRs

No external contributions found.