Learn machine learning the fun way, with Oracle and RedBull Racing

Overview

Red Bull Racing Analytics Hands-On Labs

License: UPL Quality gate

Introduction

Are you interested in learning machine learning (ML)? How about doing this in the context of the exciting world of F1 racing?! Get your ML skills bootstrapped here with Oracle and Red Bull Racing!

Red Bull F1 Race Car

This tutorial teaches ML analytics with a series of hands-on labs (HOLs) using the Data Science service in Oracle Cloud Infrastructure.

You'll learn how to get data from some public data sources, then how to analyze this data using some of the latest ML techniques. In the process you'll build ML models and test them out in a predictor app.

Getting Started

There is some infrastructure that must be deployed before you can enjoy this tutorial. See the Terraform documentation for more information.

After the OCI infrastructure is deployed, proceed with the beginner's tutorial to start through the ML labs.

Prerequisites

You must have an OCI account. Click here to create a new cloud account.

This solution is designed to work with several OCI services, allowing you to quickly be up-and-running:

There are required OCI resources (see the Terraform documentation for more information) that are needed for this tutorial.

Notes/Issues

None at this time.

URLs

Contributing

This project is open source. Please submit your contributions by forking this repository and submitting a pull request! Oracle appreciates any contributions that are made by the open source community.

License

Copyright (c) 2021 Oracle and/or its affiliates.

Licensed under the Universal Permissive License (UPL), Version 1.0.

See LICENSE for more details.

Comments
  • Refactored Terraform code

    Refactored Terraform code

    • Compatible with ORM, Cloud Shell and Terraform CLI
    • Updated README to include instructions for all three methods
    • Refactored, removing unnecessary resources (Vault, public Subnet, etc.).
    • Added a nerd knob so that it could use an existing Group (rather than create a new one)
    • Fixed ORM RegEx filters to allow dashes (-) and underscores (_), for the names
    opened by timclegg 2
  • Issue with hands on lab guide - launchapp.sh missing

    Issue with hands on lab guide - launchapp.sh missing

    https://github.com/oracle-devrel/redbull-analytics-hol/tree/main/beginners#beginners-hands-on-lab

    In Starting The Web Application it reads:

    cd /home/opc/redbull-analytics-hol/beginners/web ./launchapp.sh start

    However is launchapp.sh is missing, for example

    (redbullenv) cd /home/opc/redbull-analytics-hol/beginners/web (redbullenv) ./launchapp.sh start bash: ./launchapp.sh: No such file or directory

    opened by raekins 1
  • fix: Updating schema.yaml syntax

    fix: Updating schema.yaml syntax

    Making the variable notation follow what the doc syntax shows (https://docs.oracle.com/en-us/iaas/Content/ResourceManager/Concepts/terraformconfigresourcemanager_topic-schema.htm)

    opened by timclegg 1
  • Exploratory Data Analysis Merge Issue

    Exploratory Data Analysis Merge Issue

    Hello I have been encountering an issue while running the lab. The Jupyter notebook 03.f1_analysis_EDA.ipynb has the following issue on cell number 5:


    ValueError Traceback (most recent call last) in ----> 1 df1 = pd.merge(races,results,how='inner',on=['raceId']) 2 df2 = pd.merge(df1,quali,how='inner',on=['raceId','driverId','constructorId']) 3 df3 = pd.merge(df2,drivers,how='inner',on=['driverId']) 4 df4 = pd.merge(df3,constructors,how='inner',on=['constructorId']) 5 df5 = pd.merge(df4,circuit,how='inner',on=['circuitId'])

    ~/redbullenv/lib64/python3.6/site-packages/pandas/core/reshape/merge.py in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate) 85 copy=copy, 86 indicator=indicator, ---> 87 validate=validate, 88 ) 89 return op.get_result()

    ~/redbullenv/lib64/python3.6/site-packages/pandas/core/reshape/merge.py in init(self, left, right, how, on, left_on, right_on, axis, left_index, right_index, sort, suffixes, copy, indicator, validate) 654 # validate the merge keys dtypes. We may need to coerce 655 # to avoid incompatible dtypes --> 656 self._maybe_coerce_merge_keys() 657 658 # If argument passed to validate,

    ~/redbullenv/lib64/python3.6/site-packages/pandas/core/reshape/merge.py in _maybe_coerce_merge_keys(self) 1163 inferred_right in string_types and inferred_left not in string_types 1164 ): -> 1165 raise ValueError(msg) 1166 1167 # datetimelikes must match exactly

    ValueError: You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat

    I’m using an oracle automatic deployment provided by oracle as part of their environment. I do not have a lot of experience with Python but one possible ible solution is to read the numeric values form the csv file as integer or float but I’m almost certain the solution might be a little more elaborated than that 😉. Anyway thanks for your time. I’m really excited to test your solution and finish the lab. Thanks again.

    opened by yankodavila 2
  • Has the PAR for the stack deploy image expired.

    Has the PAR for the stack deploy image expired.

    Cannot deploy stack as getting PAR expired message.

    2021/11/07 10:50:11[TERRAFORM_CONSOLE] [INFO] Error Message: work request did not succeed, workId: ocid1.coreservicesworkrequest.oc1.eu-amsterdam-1.abqw2ljrwz2n7qqj7ghdwtnlrqol355oumc7a6coushvgdrebskspaewh7ea, entity: image, action: CREATED. Message: Import image not found: PAR is invalid (maybe is expired or deleted), please check.

    PAR in stack file is https://objectstorage.eu-frankfurt-1.oraclecloud.com/p/khhPjc_IMuyBOMfZUcJajIzCpoZ5aC-D7VMCU__GVZRlIQueXLIIcaaqLOZIuT1a/n/emeasespainsandbox/b/publichol/o/redbullhol-20210809-1523

    opened by Mel-A-M 1
Releases(v0.1.8)
Owner
Oracle DevRel
Oracle DevRel
Data-sets from the survey and analysis

bachelor-thesis "Umfragewerte.xlsx" contains the orginal survey results. "umfrage_alle.csv" contains the survey results but one participant is cancele

1 Jan 26, 2022
CubingB is a timer/analyzer for speedsolving Rubik's cubes, with smart cube support

CubingB is a timer/analyzer for speedsolving Rubik's cubes (and related puzzles). It focuses on supporting "smart cubes" (i.e. bluetooth cubes) for recording the exact moves of a solve in real time.

Zach Wegner 5 Sep 18, 2022
MeSH2Matrix - A set of Python codes for the generation of biomedical ontologies from the MeSH keywords of the PubMed scholarly publications

A set of Python codes for the generation of biomedical ontologies from the MeSH keywords of the PubMed scholarly publications

SisonkeBiotik 6 Nov 30, 2022
A set of procedures that can realize covid19 virus detection based on blood.

A set of procedures that can realize covid19 virus detection based on blood.

Nuyoah-xlh 3 Mar 07, 2022
PCAfold is an open-source Python library for generating, analyzing and improving low-dimensional manifolds obtained via Principal Component Analysis (PCA).

PCAfold is an open-source Python library for generating, analyzing and improving low-dimensional manifolds obtained via Principal Component Analysis (PCA).

Burn Research 4 Oct 13, 2022
A computer algebra system written in pure Python

SymPy See the AUTHORS file for the list of authors. And many more people helped on the SymPy mailing list, reported bugs, helped organize SymPy's part

SymPy 9.9k Dec 31, 2022
Bamboolib - a GUI for pandas DataFrames

Community repository of bamboolib bamboolib is joining forces with Databricks. For more information, please read our announcement. Please note that th

Tobias Krabel 863 Jan 08, 2023
Advanced Pandas Vault — Utilities, Functions and Snippets (by @firmai).

PandasVault ⁠— Advanced Pandas Functions and Code Snippets The only Pandas utility package you would ever need. It has no exotic external dependencies

Derek Snow 374 Jan 07, 2023
Desafio proposto pela IGTI em seu bootcamp de Cloud Data Engineer

Desafio Modulo 4 - Cloud Data Engineer Bootcamp - IGTI Objetivos Criar infraestrutura como código Utuilizando um cluster Kubernetes na Azure Ingestão

Otacilio Filho 4 Jan 23, 2022
A collection of learning outcomes data analysis using Python and SQL, from DQLab.

Data Analyst with PYTHON Data Analyst berperan dalam menghasilkan analisa data serta mempresentasikan insight untuk membantu proses pengambilan keputu

6 Oct 11, 2022
A crude Hy handle on Pandas library

Quickstart Hyenas is a curde Hy handle written on top of Pandas API to allow for more elegant access to data-scientist's powerhouse that is Pandas. In

Peter Výboch 4 Sep 05, 2022
Python utility to extract differences between two pandas dataframes.

Python utility to extract differences between two pandas dataframes.

Jaime Valero 8 Jan 07, 2023
Developed for analyzing the covariance for OrcVIO

about This repo is developed for analyzing the covariance for OrcVIO environment setup platform ubuntu 18.04 using conda conda env create --file envir

Sean 1 Dec 08, 2021
Projects that implement various aspects of Data Engineering.

DATAWAREHOUSE ON AWS The purpose of this project is to build a datawarehouse to accomodate data of active user activity for music streaming applicatio

2 Oct 14, 2021
Sentiment analysis on streaming twitter data using Spark Structured Streaming & Python

Sentiment analysis on streaming twitter data using Spark Structured Streaming & Python This project is a good starting point for those who have little

Himanshu Kumar singh 2 Dec 04, 2021
Handle, manipulate, and convert data with units in Python

unyt A package for handling numpy arrays with units. Often writing code that deals with data that has units can be confusing. A function might return

The yt project 304 Jan 02, 2023
ASOUL直播间弹幕抓取&&数据分析

ASOUL直播间弹幕抓取&&数据分析(更新中) 这些文件用于爬取ASOUL直播间的弹幕(其他直播间也可以)和其他信息,以及简单的数据分析生成。

159 Dec 10, 2022
Creating a statistical model to predict 10 year treasury yields

Predicting 10-Year Treasury Yields Intitially, I wanted to see if the volatility in the stock market, represented by the VIX index (data source), had

10 Oct 27, 2021
Techdegree Data Analysis Project 2

Basketball Team Stats Tool In this project you will be writing a program that reads from the "constants" data (PLAYERS and TEAMS) in constants.py. Thi

2 Oct 23, 2021
Data cleaning tools for Business analysis

Datacleaning datacleaning tools for Business analysis This program is made for Vicky's work. You can use it, too. 数据清洗 该数据清洗工具是为了商业分析 这个程序是为了Vicky的工作而

Lin Jian 3 Nov 16, 2021