๐ ๐ง๐ผ๐ฝ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐ฉ๐ถ๐ฟ๐๐๐ฎ๐น ๐๐ป๐๐ฒ๐ฟ๐ป๐๐ต๐ถ๐ฝ๐ โ ๐๐ฅ๐๐ & ๐ข๐ป๐น๐ถ๐ป๐ฒ๐
Boost your resume with real-world experience from global giants! ๐ผ๐
๐น Deloitte โ https://pdlink.in/4iKcgA4
๐น Accenture โ https://pdlink.in/44pfljI
๐น TATA โ https://pdlink.in/3FyjDgp
๐น BCG โ https://pdlink.in/4lyeRyY
โจ 100% Virtual
๐ Certificate Included
๐ Flexible Timings
๐ Great for Beginners & Students
Apply now and gain an edge in your career! ๐๐
Boost your resume with real-world experience from global giants! ๐ผ๐
๐น Deloitte โ https://pdlink.in/4iKcgA4
๐น Accenture โ https://pdlink.in/44pfljI
๐น TATA โ https://pdlink.in/3FyjDgp
๐น BCG โ https://pdlink.in/4lyeRyY
โจ 100% Virtual
๐ Certificate Included
๐ Flexible Timings
๐ Great for Beginners & Students
Apply now and gain an edge in your career! ๐๐
Forwarded from Artificial Intelligence
๐๐ฅ๐๐ ๐ข๐ป๐น๐ถ๐ป๐ฒ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ง๐ผ ๐๐ป๐ฟ๐ผ๐น๐น ๐๐ป ๐ฎ๐ฌ๐ฎ๐ฑ ๐
Learn Fundamental Skills with Free Online Courses & Earn Certificates
SQL:- https://pdlink.in/4lvR4zF
AWS:- https://pdlink.in/4nriVCH
Cybersecurity:- https://pdlink.in/3T6pg8O
Data Analytics:- https://pdlink.in/43TGwnM
Enroll for FREE & Get Certified ๐
Learn Fundamental Skills with Free Online Courses & Earn Certificates
SQL:- https://pdlink.in/4lvR4zF
AWS:- https://pdlink.in/4nriVCH
Cybersecurity:- https://pdlink.in/3T6pg8O
Data Analytics:- https://pdlink.in/43TGwnM
Enroll for FREE & Get Certified ๐
๐ฆ๐๐ฎ๐ฟ๐ ๐ฎ ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ ๐ถ๐ป ๐๐ฎ๐๐ฎ ๐ผ๐ฟ ๐ง๐ฒ๐ฐ๐ต (๐๐ฟ๐ฒ๐ฒ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฃ๐ฎ๐๐ต)๐
Dreaming of a career in data or tech but donโt know where to begin?๐จโ๐ป๐
Donโt worry โ this step-by-step FREE learning path will guide you from scratch to job-ready, without spending a rupee! ๐ป๐ผ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/45HFUDh
Enjoy Learning โ ๏ธ
Dreaming of a career in data or tech but donโt know where to begin?๐จโ๐ป๐
Donโt worry โ this step-by-step FREE learning path will guide you from scratch to job-ready, without spending a rupee! ๐ป๐ผ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/45HFUDh
Enjoy Learning โ ๏ธ
โค1
10 Ways to Speed Up Your Python Code
1. List Comprehensions
numbers = [x**2 for x in range(100000) if x % 2 == 0]
instead of
numbers = []
for x in range(100000):
if x % 2 == 0:
numbers.append(x**2)
2. Use the Built-In Functions
Many of Pythonโs built-in functions are written in C, which makes them much faster than a pure python solution.
3. Function Calls Are Expensive
Function calls are expensive in Python. While it is often good practice to separate code into functions, there are times where you should be cautious about calling functions from inside of a loop. It is better to iterate inside a function than to iterate and call a function each iteration.
4. Lazy Module Importing
If you want to use the time.sleep() function in your code, you don't necessarily need to import the entire time package. Instead, you can just do from time import sleep and avoid the overhead of loading basically everything.
5. Take Advantage of Numpy
Numpy is a highly optimized library built with C. It is almost always faster to offload complex math to Numpy rather than relying on the Python interpreter.
6. Try Multiprocessing
Multiprocessing can bring large performance increases to a Python script, but it can be difficult to implement properly compared to other methods mentioned in this post.
7. Be Careful with Bulky Libraries
One of the advantages Python has over other programming languages is the rich selection of third-party libraries available to developers. But, what we may not always consider is the size of the library we are using as a dependency, which could actually decrease the performance of your Python code.
8. Avoid Global Variables
Python is slightly faster at retrieving local variables than global ones. It is simply best to avoid global variables when possible.
9. Try Multiple Solutions
Being able to solve a problem in multiple ways is nice. But, there is often a solution that is faster than the rest and sometimes it comes down to just using a different method or data structure.
10. Think About Your Data Structures
Searching a dictionary or set is insanely fast, but lists take time proportional to the length of the list. However, sets and dictionaries do not maintain order. If you care about the order of your data, you canโt make use of dictionaries or sets.
1. List Comprehensions
numbers = [x**2 for x in range(100000) if x % 2 == 0]
instead of
numbers = []
for x in range(100000):
if x % 2 == 0:
numbers.append(x**2)
2. Use the Built-In Functions
Many of Pythonโs built-in functions are written in C, which makes them much faster than a pure python solution.
3. Function Calls Are Expensive
Function calls are expensive in Python. While it is often good practice to separate code into functions, there are times where you should be cautious about calling functions from inside of a loop. It is better to iterate inside a function than to iterate and call a function each iteration.
4. Lazy Module Importing
If you want to use the time.sleep() function in your code, you don't necessarily need to import the entire time package. Instead, you can just do from time import sleep and avoid the overhead of loading basically everything.
5. Take Advantage of Numpy
Numpy is a highly optimized library built with C. It is almost always faster to offload complex math to Numpy rather than relying on the Python interpreter.
6. Try Multiprocessing
Multiprocessing can bring large performance increases to a Python script, but it can be difficult to implement properly compared to other methods mentioned in this post.
7. Be Careful with Bulky Libraries
One of the advantages Python has over other programming languages is the rich selection of third-party libraries available to developers. But, what we may not always consider is the size of the library we are using as a dependency, which could actually decrease the performance of your Python code.
8. Avoid Global Variables
Python is slightly faster at retrieving local variables than global ones. It is simply best to avoid global variables when possible.
9. Try Multiple Solutions
Being able to solve a problem in multiple ways is nice. But, there is often a solution that is faster than the rest and sometimes it comes down to just using a different method or data structure.
10. Think About Your Data Structures
Searching a dictionary or set is insanely fast, but lists take time proportional to the length of the list. However, sets and dictionaries do not maintain order. If you care about the order of your data, you canโt make use of dictionaries or sets.
โค3
Forwarded from Python Projects & Resources
๐๐๐ฆ๐๐ข ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐๐
- Data Analytics
- Data Science
- Python
- Javascript
- Cybersecurity
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4fYr1xO
Enroll For FREE & Get Certified๐
- Data Analytics
- Data Science
- Python
- Javascript
- Cybersecurity
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4fYr1xO
Enroll For FREE & Get Certified๐
Azure_Data_Factory_by_Example_Practical_Implementation.pdf
10.8 MB
Azure Data Factory by Example
Richard Swinbank, 2021
Richard Swinbank, 2021
Azure Data Engineering Cookbook (SafefilekU.com).pdf
55.7 MB
Azure Data Engineering Cookbook
Nagaraj Venkatesan, 2022
Nagaraj Venkatesan, 2022
Hands-on Guide to Apache Spark 3 (2024).pdf
11.2 MB
Hands-on Guide to Apache Spark 3
Alfonso Antolรญnez Garcรญa, 2023
Alfonso Antolรญnez Garcรญa, 2023
๐ฅ2โค1
Forwarded from Artificial Intelligence
๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฅ๐๐ ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ ,๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ,๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐๐ & ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐๐๐ถ๐ฑ๐ฒ๐
Roadmap:- https://pdlink.in/41c1Kei
Certifications:- https://pdlink.in/3Fq7E4p
Projects:- https://pdlink.in/3ZkXetO
Interview Q/A :- https://pdlink.in/4jLOJ2a
Enroll For FREE & Become a Certified Data Analyst In 2025๐
Roadmap:- https://pdlink.in/41c1Kei
Certifications:- https://pdlink.in/3Fq7E4p
Projects:- https://pdlink.in/3ZkXetO
Interview Q/A :- https://pdlink.in/4jLOJ2a
Enroll For FREE & Become a Certified Data Analyst In 2025๐
Effective Communication of Data Insights (Very Important Skill for Data Analysts)
Know Your Audience:
Tip: Tailor your presentation based on the technical expertise and interests of your audience.
Consideration: Avoid jargon when presenting to non-technical stakeholders.
Focus on Key Insights:
Tip: Highlight the most relevant findings and their impact on business goals.
Consideration: Avoid overwhelming your audience with excessive details or raw data.
Use Visuals to Support Your Message:
Tip: Leverage charts, graphs, and dashboards to make your insights more digestible.
Consideration: Ensure visuals are simple and easy to interpret.
Tell a Story:
Tip: Present data in a narrative form to make it engaging and memorable.
Consideration: Use the context of the data to tell a clear story with a beginning, middle, and end.
Provide Actionable Recommendations:
Tip: Focus on practical steps or decisions that can be made based on the data.
Consideration: Offer clear, actionable insights that drive business outcomes.
Be Transparent About Limitations:
Tip: Acknowledge any data limitations or assumptions in your analysis.
Consideration: Being transparent builds trust and shows a thorough understanding of the data.
Encourage Questions:
Tip: Allow for questions and discussions to clarify any doubts.
Consideration: Engage with your audience to ensure full understanding of the insights.
You can find more communication tips here: https://t.me/englishlearnerspro
I have curated Data Analytics Resources ๐๐
https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
Like this post for more content like this ๐โฅ๏ธ
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
Know Your Audience:
Tip: Tailor your presentation based on the technical expertise and interests of your audience.
Consideration: Avoid jargon when presenting to non-technical stakeholders.
Focus on Key Insights:
Tip: Highlight the most relevant findings and their impact on business goals.
Consideration: Avoid overwhelming your audience with excessive details or raw data.
Use Visuals to Support Your Message:
Tip: Leverage charts, graphs, and dashboards to make your insights more digestible.
Consideration: Ensure visuals are simple and easy to interpret.
Tell a Story:
Tip: Present data in a narrative form to make it engaging and memorable.
Consideration: Use the context of the data to tell a clear story with a beginning, middle, and end.
Provide Actionable Recommendations:
Tip: Focus on practical steps or decisions that can be made based on the data.
Consideration: Offer clear, actionable insights that drive business outcomes.
Be Transparent About Limitations:
Tip: Acknowledge any data limitations or assumptions in your analysis.
Consideration: Being transparent builds trust and shows a thorough understanding of the data.
Encourage Questions:
Tip: Allow for questions and discussions to clarify any doubts.
Consideration: Engage with your audience to ensure full understanding of the insights.
You can find more communication tips here: https://t.me/englishlearnerspro
I have curated Data Analytics Resources ๐๐
https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
Like this post for more content like this ๐โฅ๏ธ
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
โค1
๐๐ป๐ฑ๐๐๐๐ฟ๐ ๐๐ฝ๐ฝ๐ฟ๐ผ๐๐ฒ๐ฑ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ๐
Whether youโre interested in AI, Data Analytics, Cybersecurity, or Cloud Computing, thereโs something here for everyone.
โ 100% Free Courses
โ Govt. Incentives on Completion
โ Self-paced Learning
โ Certificates to Showcase on LinkedIn & Resume
โ Mock Assessments to Test Your Skills
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/447coEk
Enroll for FREE & Get Certified ๐
Whether youโre interested in AI, Data Analytics, Cybersecurity, or Cloud Computing, thereโs something here for everyone.
โ 100% Free Courses
โ Govt. Incentives on Completion
โ Self-paced Learning
โ Certificates to Showcase on LinkedIn & Resume
โ Mock Assessments to Test Your Skills
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/447coEk
Enroll for FREE & Get Certified ๐
๐ง๐ผ๐ฝ ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐ & ๐๐ฒ๐ฎ๐ฑ๐ถ๐ป๐ด ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐ ๐ข๐ณ๐ณ๐ฒ๐ฟ๐ถ๐ป๐ด ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
Harward :- https://pdlink.in/4kmYOn1
MIT :- https://pdlink.in/45cvR95
HP :- https://pdlink.in/45ci02k
Google :- https://pdlink.in/3YsujTV
Microsoft :- https://pdlink.in/441GCKF
Standford :- https://pdlink.in/3ThPwNw
IIM :- https://pdlink.in/4nfXDrV
Enroll for FREE & Get Certified ๐
Harward :- https://pdlink.in/4kmYOn1
MIT :- https://pdlink.in/45cvR95
HP :- https://pdlink.in/45ci02k
Google :- https://pdlink.in/3YsujTV
Microsoft :- https://pdlink.in/441GCKF
Standford :- https://pdlink.in/3ThPwNw
IIM :- https://pdlink.in/4nfXDrV
Enroll for FREE & Get Certified ๐
Forwarded from Artificial Intelligence
๐๐ข๐๐ซ๐จ๐ฌ๐จ๐๐ญ ๐
๐๐๐ ๐๐๐ซ๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐๐จ๐ฎ๐ซ๐ฌ๐๐ฌ!๐๐ป
Supercharge your career with 5 FREE Microsoft certification courses designed to boost your data analytics skills!
๐๐ง๐ซ๐จ๐ฅ๐ฅ ๐ ๐จ๐ซ ๐ ๐๐๐๐ :-
https://bit.ly/3Vlixcq
- Earn certifications to showcase your skills
Donโt waitโstart your journey to success today! โจ
Supercharge your career with 5 FREE Microsoft certification courses designed to boost your data analytics skills!
๐๐ง๐ซ๐จ๐ฅ๐ฅ ๐ ๐จ๐ซ ๐ ๐๐๐๐ :-
https://bit.ly/3Vlixcq
- Earn certifications to showcase your skills
Donโt waitโstart your journey to success today! โจ
โค1
How_to_kickstart_an_azure_data_engineering_project_1751578967.pdf
393.7 KB
Dear Data Fam,
If you are looking to kick start Azure Data Engineering from Starch , check out this document !!
It will help you to understand a basic end to end prod flow
If you are looking to kick start Azure Data Engineering from Starch , check out this document !!
It will help you to understand a basic end to end prod flow
โค2
๐๐ฟ๐ฒ๐ฒ ๐๐ & ๐ ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐๐ผ๐๐ฟ๐๐ฒ ๐ณ๐ผ๐ฟ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ๐๐
Want to explore AI & Machine Learning but donโt know where to start โ or donโt want to spend โนโนโน on it?๐จโ๐ป
Learn the foundations of AI, machine learning basics, data handling, and real-world use cases in just a few hours.๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/401SWry
This 100% FREE course is designed just for beginners โ whether youโre a student, fresher, or career switcherโ ๏ธ
Want to explore AI & Machine Learning but donโt know where to start โ or donโt want to spend โนโนโน on it?๐จโ๐ป
Learn the foundations of AI, machine learning basics, data handling, and real-world use cases in just a few hours.๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/401SWry
This 100% FREE course is designed just for beginners โ whether youโre a student, fresher, or career switcherโ ๏ธ