Data Collection Stratergy For Machine Learning Projects With API's- RapidAPI

Summary

In this insightful video, Krishnaik introduces Rapid API, a platform offering access to a multitude of public datasets, as a valuable resource for data science projects. Highlighting the importance of end-to-end projects for acing data science interviews, he demonstrates how Rapid API can simplify data collection strategies, moving beyond reliance on open-source datasets. By showcasing practical examples, including fetching COVID-19 statistics and financial market data, Krishnaik guides viewers through creating data pipelines and storing data in databases. This video serves as a comprehensive guide for data scientists seeking to enhance their projects with diverse data sources, underlining the significance of effective data collection in solving real-world problems.

Takeaways

• 📚 The importance of implementing end-to-end data science projects for cracking data science interviews is emphasized.
• 📈 Focus on data collection strategies is highlighted as a crucial area where many aspirants face confusion and rely heavily on open-source datasets from platforms like Kaggle.
• 📱 Introduction to Rapid API as a valuable resource for exploring publicly available datasets and creating data pipeline architectures.
• 🚀 The process of requirement gathering in data science projects involves discussions between domain experts, product owners, and business analysts to define tasks and subtasks.
• 🔍 Explains the role of third-party Cloud APIs in data collection and the possibility of relying on internal databases or creating IoT solutions for unique datasets.
• 📅 Demonstrates how to use Rapid API to access and implement data collection from public and private APIs into data science projects.
• 💻 Provides practical guidance on executing API calls using Python code snippets and storing the data in databases like SQL or NoSQL.
• 📗 Showcases the versatility of Rapid API for various use cases, including accessing COVID-19 statistics, movie databases, and financial news.
• 🚡 Offers insights into monetizing APIs by creating and publishing them on Rapid API, including a subscription model for access.
• 📲 Discusses the ease of integrating API data into real-world industry projects, enhancing data collection strategies and processing for actionable insights.

Q & A

Why does the speaker emphasize the importance of end-to-end data science projects for interviews?

The speaker emphasizes the importance of end-to-end data science projects for interviews because they demonstrate a candidate's practical experience across various modules, showcasing their ability to work on real-world problems.

What challenge do many people face in the data collection phase of data science projects according to the speaker?

According to the speaker, many people face challenges in the data collection phase due to confusion and reliance on open source datasets and datasets from Kaggle, lacking experience in gathering data through other means.

What solution does the speaker offer for overcoming data collection challenges in data science projects?

The speaker introduces Rapid API as a solution for overcoming data collection challenges, suggesting it as a platform to explore publicly available datasets and create data pipeline architectures.

What is the first step in a data science project lifecycle as described by the speaker?

The first step in a data science project lifecycle, as described by the speaker, is 'Requirement Gathering', where domain experts, product owners, and business analysts discuss, jot down requirements, and divide tasks.

How does the speaker suggest one can use Rapid API in data science projects?

The speaker suggests using Rapid API to access a variety of public and private APIs, which can provide data for different use cases, thereby facilitating the data collection strategy in data science projects.

Can you create your own API on Rapid API according to the speaker?

Yes, according to the speaker, you can create your own API and upload it to Rapid API, which allows for both the use of public APIs and the sharing of your own APIs on the platform.

What example does the speaker give to demonstrate the use of Rapid API in fetching data?

The speaker demonstrates fetching data using Rapid API with an example of accessing COVID-19 statistics through a specific API, showing how to execute the request and process the data.

How does the speaker suggest handling continuous data updates in a database?

The speaker suggests setting up a cron job to regularly check for new data updates at specific times and upload them to the database, ensuring continuous data flow for the project.

What are the benefits of using public APIs for data collection as mentioned by the speaker?

The benefits of using public APIs for data collection include access to a wide range of data sets, ease of integration into data pipelines, and the ability to handle real-world, industry-relevant projects more effectively.

Does the speaker provide any caution or advice when using APIs for data collection in projects?

While the speaker primarily focuses on the advantages of using APIs like Rapid API, they suggest starting with public APIs and considering the pricing and terms of use when moving to more extensive or commercial API usage.

Outlines

00:00

📊 Data Collection Strategies for Data Science Projects

Krish Naik emphasizes the importance of implementing end-to-end data science projects for cracking data science interviews, focusing on the often confusing aspect of data collection. He introduces RapidAPI as a valuable resource for accessing a wide range of publicly available datasets, which can help in building robust data pipeline architectures. Naik outlines the initial steps of a data science project, including requirement gathering and the selection of datasets, either from internal databases or third-party cloud APIs. He demonstrates how RapidAPI allows users to explore various datasets and APIs for different use cases, including COVID-19 statistics and market information, and shows how to integrate these data sources into projects, highlighting the practical application in industry-ready projects.

05:02

🔍 Utilizing RapidAPI for Real-World Data Science Solutions

In this section, Krish Naik dives deeper into how RapidAPI can be leveraged for effective data collection and integration into data science projects. He showcases the simplicity of using RapidAPI to fetch data from various APIs, including health data and market news, and discusses how this data can be pre-processed and stored in databases like MongoDB. Naik also touches on the potential of using paid APIs through RapidAPI for more specific data needs and the opportunity to create and monetize personal APIs on the platform. He concludes by encouraging the use of public APIs for practical data science projects and hints at the possibility of earning from custom APIs, making a strong case for the role of RapidAPI in simulating real-world industry scenarios and enhancing project portfolios.

Keywords

💡data collection strategies

Refers to methods and techniques for gathering relevant data to solve a data science or machine learning problem. The video discusses using public APIs as an effective data collection strategy instead of always relying on open source datasets.

💡API

Stands for Application Programming Interface. Allows different software applications to communicate with each other by calling features and services. The video introduces RapidAPI as a platform providing various public APIs that can be used for data collection.

💡real world industry project

Refers to data science and machine learning projects that aim to solve practical business problems in different industries. Using public APIs to collect industry data mirrors real world scenarios.

💡rapidAPI

Name of the API platform introduced in the video. Provides access to various public API sets that can be used through code snippets in different programming languages.

💡data pipeline

Refers to the end-to-end flow of data from its source to business insights. Can include data collection, storage, processing etc. Public APIs can feed into data pipelines.

💡cloud

The public APIs discussed are hosted on cloud infrastructure. Cloud provides on-demand access to computing services, databases, storage etc over the internet.

💡use case

A specific business problem being solved using data science and ML. The video mentions public APIs allow solving use cases across different sectors by providing relevant data.

💡iot

Acronym for Internet of Things. Connected devices and sensors that generate data. The video mentions creating your own IOT data as an alternative data collection strategy.

💡JSON format

Standard data interchange format to transmit data objects. Public API responses are shown in JSON format which can then be loaded into databases.

💡endpoints

Refers to the different API calls available. RapidAPI provides metadata on endpoints like example responses to help test APIs.

Highlights

RapidAPI allows you to explore publicly available datasets through APIs

You can create data pipelines by taking data from RapidAPI APIs and storing it in databases

Data collection strategy and identifying datasets are very important

RapidAPI has public and private APIs - you can create your own private API

Public APIs on RapidAPI provide access to useful datasets like COVID-19 stats

RapidAPI code snippets allow easy access to APIs from various programming languages

The JSON data from APIs can be stored in databases like MongoDB after preprocessing

RapidAPI has top popular public APIs like sports, movies, financial news etc

The Bloomberg API allows accessing market and financial data very easily

You can also earn money by creating your own API and publishing it on RapidAPI

Using public APIs makes data collection similar to real-world industry projects

You can schedule jobs to continuously get updated data from APIs

Using RapidAPI showcases your ability to implement end-to-end data pipelines

Public APIs save time compared to creating own IoT systems for data collection

RapidAPI makes implementing data science projects very easy

Transcripts

hello all my name is krishnaik and

welcome to my YouTube channel so guys uh

in many of my videos I've actually told

you that implementing end-to-end data

science project is super important for

cracking data science interviews because

the interviewer will get to know that

which all modules you have specifically

worked yes there are many people who

work absolutely fine in all the modules

but in one module that is in the data

collection strategies they have a lot of

confusion they're still dependent on

open source data sets and data sets from

kaggle so today in this particular video

I'm going to introduce you about one API

that is called as rapid API from where

you can probably explore a lot of data

sets which are publicly available and

you can actually create a lot of data

pipeline architecture like taking that

but from that particular API taking up

the data and storing it in some

databases so please make sure that you

watch this video till the end because

data collection strategy is also very

important identifying data set is also

very important okay so without wasting

any time let's go ahead and let me share

my screen over here so so I've already

made sure that I've explained you about

the data science roadmap just recently

uh two to three days back but first of

all let's understand the work of a data

scientist so guys initially when a data

science project is basically coming the

first step is basically requirement

Gatherings where the domain expert is a

product owner team along with the

business analyst team will have a lot of

discussion they will jot down all the

requirements use some tools like jira or

Confluence divide all the tasks and

subtask in Sprints and then they will

provide all these requirements to the

data analyst and data scientist team

which is in this step too then this with

the domain expert and product owner will

have a discussion to identify the data

set to solve this particular problem

they may be dependent on the internal

database or they may be dependent on the

third party Cloud API right now when I

say third-party Cloud API many people

have actually asked me what is this

third party Cloud API private uh like it

will also be paid so what are this

specific data okay there are multiple

ways guys you can also probably create

your own iot team and probably start

creating the data set with respect to

your products and do it but there are

many business use cases that are common

right in service based companies you may

get projects from different different

sectors itself and based on that your

data may be changing right now with

respect to that I have actually checked

out this rapid API platform wherein you

will be able to see some amazing public

data set again guys this is not a

sponsored video but I was able to find

it out and this will be super important

for you all to solve different different

use cases so over here what you can

basically do just login over here and

with respect to the login like Google

login you can actually do and after

going over here here you'll be able to

see public Avis and private apis private

apis basically means you can also create

your API and you can probably do it or

upload it over here right and basically

like you're creating a API deploying it

in a cloud and you can put that specific

API over here if you want that specific

video also you can let me know just in a

couple of days I'll also try to upload

that particular video so just write down

in the comment how to create your own

private API and how to publish in the

rapid API but other than that suppose if

you want to play with public API you can

go over here so let's say that I want to

try any of the specific apis let's say

with respect to covid-19 I am actually

getting this particular API and now this

particular API will get loaded here you

will get everything like what all apis

being provided over here you can have

country statistics history and over here

you basically have the code snippet

suppose let's say if I go to Python and

probably just select on request right

and this is also having all the other

programming language you can probably

get the entire code itself and let's say

this is the code I want to run and here

I can also test it with test endpoints

okay so once I test it you can see that

I'm getting all the information right so

suppose if I probably go in the code

snippet I take this up and what I do I

go over here in my vs code I will just

go and execute it I will clear my screen

okay and after clearing my screen I'll

just save it over here and I will write

python app.py right so here you'll be

able to see that I will be also able to

get the output now this entire

information I can probably store it in

the database or take it in any kind of

database like nosql SQL database it is

up to you based on the requirement but

here am I able to get the entire output

or from that specific API so my data

collection strategies now becomes very

simple right I don't have to be

dependent on anything else I and this

also looks amazing because this is what

in the real world scenario also we do in

Industry ready Pro when we are solving

some industry ready projects we have to

be dependent on third party apis because

this apis will continuously giving us

data with respect to dates right not

only that let's say I want to drive with

Statistics now you just see I clicked on

strategies the entire code changed I'm

just going to copy the code you can also

test the end point over here and based

on the test I will be able to get all

the answers you can see that I'm getting

with respect to every country countries

how many cases were there how many

deaths were there how many tests are

there everything right so I will just go

ahead and execute it over here same code

I'll paste it over here save it and then

I will just go and clear the screen now

see this how easily I'm able to use this

entire rapid API right so I'm just going

to write Python app.py and finally

you'll be able to see I'm getting all

the output now what I can do I can

probably take this output do some

pre-processing and store it in the

mongodb right it is obviously in the

Json format if you directly put in the

mongodb you will be able to get the

output like this only right with also

respect to all the records right this is

how you can basically try it out again

guys here you also have paid API so

suppose if I probably go to Rapid API I

want something else let's say free

public API for Developers

so here I have top 50 most popular apis

right you have API football Movie

Database now see many many of you

implement movie recommendation system

why can't you directly use the movie

database from here

and from there the data collection

strategy is more about reading from some

apis storing it in the data databases

doing some pre-processing and all see

now here you have Bloomberg market and

financial news API documentation let's

try this also uh we have cloned this API

to another at this this this API itself

now here you can see here you have

Market information get movers get cross

currencies let's say I want to get

across currencies okay and I will

probably go and uh just go and get the

python code so this is my python code

you can see from this particular URL we

are able to get by using this rapid API

key right and the best thing is that you

can also create your own and you can

also get paid from this right because

there are some requests with respect to

that let me just check one more thing

over here I have to subscribe to this

particular test so once I subscribe it

here you can see Basics Pro Ultra Omega

is there if you probably create your own

API you can also select it okay and with

the help of rgbt I think it will become

very easy so I'm subscribing to the free

one now I have the code I'm executing it

over here now let's see whether I'll get

the output or not okay so I'll just go

over here I will clear the screen and

here is my python I'm dot py so finally

you'll be able to see I'm getting all

the output right isn't it very easy you

just need to do one or two rounds of

processing to get the data in the right

format and probably directly use it so

with respect to this query string all

this querences I'm able to get all the

information right so uh I hope you are

able to understand guys now if I go to

back to all the plans and probably if I

go to end points here you will be able

to also test it out entirely so any apis

over here will be there just let me know

whether you want to know that how you

can probably earn money from this

because you can also create your own API

and probably deploy it in some server

and put it over here right not only this

I have news news list new useless by

region stories list so if I probably

also execute this I will also be able to

get the information suppose if I am

solving any use case I am able to solve

most of the things right so here it is

very simple very easy and this actually

looks like a real world industry project

right so I'm just going to clear it let

me just make my face go over here right

and here you have

python app.piler right and I'll get the

response.text and probably I can also

get it in the Json format or however I

want see all the links everything is

basically over here this news article is

basically coming I can also open it over

here and see all the information

everything is there right so this is how

you can easily work on the data store

data collection strategy itself you can

design it you can use database now

you're probably thinking like you're

continuously getting the data you can

also create a chrome job every day uh

probably at some specific time you just

check the new status and probably upload

it in the database and use it right so

this is an amazing way to check it out

rapid API again this is not a sponsored

video but yes I found out this a good

way of actually showcasing your

experience even in companies if you're

probably using it try to use the public

API and then try to take the pricing

itself based on the API set right so

this was it from my side I'll see you

all in the next video have a great day

thank you mondal bye