Perhaps you wanted to describe that new algorithm that you have developed for your #machinelearning project.
You can describe them using the st.latex() method.
1/ Book overview and review
Practical Data Science with Python (By Nathan George)
𧡠See thread below #datascience#python
2/ π€ Author
- Nathan George
- Data scientist at a fintech company
- Taught at Regis University, DataCamp and Manning LiveProject
- Mentor students at Udacity AI and Machine Learning NanoDegree
3/ π Book details
- About 600 pages
- 21 Chapters
- 6 Parts
1. Data Science Starter Kit
This starter kit provides a framework that will help pinpoint you in the right direction and help you take your first steps towardsdatascience.com/data-science-sβ¦
2. How to Master Python for Data Science
This article will have navigate you through the landscape of the Python language at their intersection with data science, which will help you get started in no time. towardsdatascience.com/how-to-master-β¦
Getting started on the Open #Bioinformatics Research Project initiative
ππ§΅π See thread below
1. Watch the introductory video on the Open Bioinformatics Research Project initiative for:
- Intro to the initiative
- High-level overview of the dataset
- Ideas for which types of analysis to perform
2/ 1. Craft your own personal learning plan
Earlier this year I made a video that details the steps you can take to craft your own personal learning plan for your data journey. Everyone's plan is different, make your own! Here's how...
3/ 2. Work on data projects using datasets that is interesting to you
When starting out, I found that working on datasets that's interesting to you will help you engage in the process. Be persistent and work on the project to completion (end-to-end).
How? DataβModelβ Deployment