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 šŸ˜‰. 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
ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.

ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.

JR Oakes 36 Jan 03, 2023
Hydrogen (or other pure gas phase species) depressurization calculations

HydDown Hydrogen (or other pure gas phase species) depressurization calculations This code is published under an MIT license. Install as simple as: pi

Anders Andreasen 13 Nov 26, 2022
MS in Data Science capstone project. Studying attacks on autonomous vehicles.

Surveying Attack Models for CAVs Guide to Installing CARLA and Collecting Data Our project focuses on surveying attack models for Connveced Autonomous

Isabela Caetano 1 Dec 09, 2021
šŸ“Š Python Flask game that consolidates data from Nasdaq, allowing the user to practice buying and selling stocks.

Web Trader Web Trader is a trading website that consolidates data from Nasdaq, allowing the user to search up the ticker symbol and price of any stock

Paulina Khew 21 Aug 30, 2022
Package for decomposing EMG signals into motor unit firings, as used in Formento et al 2021.

EMGDecomp Package for decomposing EMG signals into motor unit firings, created for Formento et al 2021. Based heavily on Negro et al, 2016. Supports G

13 Nov 01, 2022
Falcon: Interactive Visual Analysis for Big Data

Falcon: Interactive Visual Analysis for Big Data Crossfilter millions of records without latencies. This project is work in progress and not documente

Vega 803 Dec 27, 2022
Open-Domain Question-Answering for COVID-19 and Other Emergent Domains

Open-Domain Question-Answering for COVID-19 and Other Emergent Domains This repository contains the source code for an end-to-end open-domain question

7 Sep 27, 2022
pipeline for migrating lichess data into postgresql

How Long Does It Take Ordinary People To "Get Good" At Chess? TL;DR: According to 5.5 years of data from 2.3 million players and 450 million games, mo

Joseph Wong 182 Nov 11, 2022
Picka: A Python module for data generation and randomization.

Picka: A Python module for data generation and randomization. Author: Anthony Long Version: 1.0.1 - Fixed the broken image stuff. Whoops What is Picka

Anthony 108 Nov 30, 2021
Anomaly Detection with R

AnomalyDetection R package AnomalyDetection is an open-source R package to detect anomalies which is robust, from a statistical standpoint, in the pre

Twitter 3.5k Dec 27, 2022
pyETT: Python library for Eleven VR Table Tennis data

pyETT: Python library for Eleven VR Table Tennis data Documentation Documentation for pyETT is located at https://pyett.readthedocs.io/. Installation

Tharsis Souza 5 Nov 19, 2022
Fit models to your data in Python with Sherpa.

Table of Contents Sherpa License How To Install Sherpa Using Anaconda Using pip Building from source History Release History Sherpa Sherpa is a modeli

134 Jan 07, 2023
PyChemia, Python Framework for Materials Discovery and Design

PyChemia, Python Framework for Materials Discovery and Design PyChemia is an open-source Python Library for materials structural search. The purpose o

Materials Discovery Group 61 Oct 02, 2022
In this project, ETL pipeline is build on data warehouse hosted on AWS Redshift.

ETL Pipeline for AWS Project Description In this project, ETL pipeline is build on data warehouse hosted on AWS Redshift. The data is loaded from S3 t

Mobeen Ahmed 1 Nov 01, 2021
Galvanalyser is a system for automatically storing data generated by battery cycling machines in a database

Galvanalyser is a system for automatically storing data generated by battery cycling machines in a database, using a set of "harvesters", whose job it

Battery Intelligence Lab 20 Sep 28, 2022
Statistical Rethinking course winter 2022

Statistical Rethinking (2022 Edition) Instructor: Richard McElreath Lectures: Uploaded Playlist and pre-recorded, two per week Discussion: Online, F

Richard McElreath 3.9k Dec 31, 2022
Analyze the Gravitational wave data stored at LIGO/VIRGO observatories

Gravitational-Wave-Analysis This project showcases how to analyze the Gravitational wave data stored at LIGO/VIRGO observatories, using Python program

1 Jan 23, 2022
InDels analysis of CRISPR lines by NGS amplicon sequencing technology for a multicopy gene family.

CRISPRanalysis InDels analysis of CRISPR lines by NGS amplicon sequencing technology for a multicopy gene family. In this work, we present a workflow

2 Jan 31, 2022
Flood modeling by 2D shallow water equation

hydraulicmodel Flood modeling by 2D shallow water equation. Refer to Hunter et al (2005), Bates et al. (2010). Diffusive wave approximation Local iner

6 Nov 30, 2022
Pandas and Spark DataFrame comparison for humans

DataComPy DataComPy is a package to compare two Pandas DataFrames. Originally started to be something of a replacement for SAS's PROC COMPARE for Pand

Capital One 259 Dec 24, 2022