Data Collection Stratergy For Machine Learning Projects With API's- RapidAPI
Summary
TLDRIn 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
📊 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.
🔍 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.
Mindmap
Keywords
💡data collection strategies
💡API
💡real world industry project
💡rapidAPI
💡data pipeline
💡cloud
💡use case
💡iot
💡JSON format
💡endpoints
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
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