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This repository contains a list of awesome open-source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning


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Data Scientist Problems and Tools 🧵

🧹 Data Cleaning - Pandas
📊 Data Visualization - Matplotlib
📈 Statistical Analysis - SciPy
🤖 Machine Learning - Scikit-Learn
🧠 Deep Learning - TensorFlow
💾 Big Data Processing - Apache Spark
📝 Natural Language Processing - NLTK
🚀 Model Deployment - Flask
🔀 Version Control - GitHub
🗄️ Data Storage - PostgreSQL
☁️ Cloud Computing - AWS
🧪 Experiment Tracking - MLflow

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AI tools for data analyst role.

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Check this video and craft the industry standard resume.

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Citi Hiring Fresher For Business Analyst
Location: Bangalore
Qualification: Bachelor's Degree
Work Experience: Fresher - 2 Years
Salary: Up to 10 LPA
Apply Link: https://jobs.citi.com/job/-/-/287/65497931696?utm_term=393693070&ss=paid&utm_campaign=apac_experienced&utm_medium=job_posting&source=linkedinJB&utm_source=linkedin.com&utm_content=social_media&dclid=CPO78YTpooYDFT-jZgIdsYYGVw

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Latest Jobs & Internship Opportunities 👇👇

📌Ascensus is hiring for Data Analyst
Expected Salary: 5 - 8 LPA
Apply here: https://careers.ascensus.com/jobs/analyst-tamil-nadu-india

📌Pinebridge is hiring for Data Scientist
Expected Salary: 6 - 10 LPA
Apply here: https://pinebridge.wd5.myworkdayjobs.com/PineBridge_Career_Site/job/Mumbai/Data-Scientist--Quantitative-Equity-Researcher-2_R-01726

📌TaskUs is hiring for Data Scientist
Expected Salary: 6 - 10 LPA
Apply here: https://jobs.eu.humanly.io/jobs/dc0f3ab1-f2e6-4da8-a803-2dcb52422ed7

📌Honeywell is hiring for Data Scientist II
Expected Salary: 20 - 40 LPA
Apply here: https://careers.honeywell.com/us/en/job/HONEUSHRD225742EXTERNALENUS/Data-Scientist-II

📌Successfactors is hiring for Data Scientist
Expected Salary: 20 - 40 LPA
Apply here: https://career10.successfactors.com/career?career_ns=job_listing&company=axtriaindiP&navBarLevel=JOB_SEARCH&rcm_site_locale=en_US&career_job_req_id=9599

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Complete topics & subtopics of hashtag #SQL for Data Analyst role:-

𝟭. 𝗕𝗮𝘀𝗶𝗰 𝗦𝗤𝗟 𝗦𝘆𝗻𝘁𝗮𝘅:
SQL keywords
Data types
Operators
SQL statements (SELECT, INSERT, UPDATE, DELETE)

𝟮. 𝗗𝗮𝘁𝗮 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗗𝗟):
CREATE TABLE
ALTER TABLE
DROP TABLE
Truncate table

𝟯. 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 (𝗗𝗠𝗟):
SELECT statement (SELECT, FROM, WHERE, ORDER BY, GROUP BY, HAVING, JOINs)
INSERT statement
UPDATE statement
DELETE statement

𝟰. 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
SUM, AVG, COUNT, MIN, MAX
GROUP BY clause
HAVING clause

𝟱. 𝗗𝗮𝘁𝗮 𝗖𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀:
Primary Key
Foreign Key
Unique
NOT NULL
CHECK

𝟲. 𝗝𝗼𝗶𝗻𝘀:
INNER JOIN
LEFT JOIN
RIGHT JOIN
FULL OUTER JOIN
Self Join
Cross Join

𝟳. 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀:
Types of subqueries (scalar, column, row, table)
Nested subqueries
Correlated subqueries

𝟴. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗤𝗟 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
String functions (CONCAT, LENGTH, SUBSTRING, REPLACE, UPPER, LOWER)
Date and time functions (DATE, TIME, TIMESTAMP, DATEPART, DATEADD)
Numeric functions (ROUND, CEILING, FLOOR, ABS, MOD)
Conditional functions (CASE, COALESCE, NULLIF)

𝟵. 𝗩𝗶𝗲𝘄𝘀:
Creating views
Modifying views
Dropping views

𝟭𝟬. 𝗜𝗻𝗱𝗲𝘅𝗲𝘀:
Creating indexes
Using indexes for query optimization

𝟭𝟭. 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝘀:
ACID properties
Transaction management (BEGIN, COMMIT, ROLLBACK, SAVEPOINT)
Transaction isolation levels

𝟭𝟮. 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆:
Data integrity constraints (referential integrity, entity integrity)
GRANT and REVOKE statements (granting and revoking permissions)
Database security best practices

𝟭𝟯. 𝗦𝘁𝗼𝗿𝗲𝗱 𝗣𝗿𝗼𝗰𝗲𝗱𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
Creating stored procedures
Executing stored procedures
Creating functions
Using functions in queries

𝟭𝟰. 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻:
Query optimization techniques (using indexes, optimizing joins, reducing subqueries)
Performance tuning best practices

𝟭𝟱. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗤𝗟 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
Recursive queries
Pivot and unpivot operations
Window functions (Row_number, rank, dense_rank, lead & lag)
CTEs (Common Table Expressions)
Dynamic SQL

𝗝𝗼𝗶𝗻 𝗺𝘆 𝗧𝗲𝗹𝗲𝗴𝗿𝗮𝗺 𝗖𝗵𝗮𝗻𝗻𝗲𝗹 - https://t.me/codingdidi

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Identifying outliers in a data science project is an important step to ensure the quality and accuracy of your analysis. Outliers can be caused by measurement errors, data entry mistakes, or even intentional manipulation. Here are some approaches you can use to identify liars in your data science project:

1. Visual Exploration: Start by visualizing your data using plots such as histograms, box plots, or scatter plots. Look for any data points that appear significantly different from the majority of the data. Outliers may appear as points that are far away from the main cluster or exhibit unusual patterns.

2. Statistical Methods: Utilize statistical methods to identify outliers. One common approach is to calculate the z-score or standard deviation of each data point and flag those that fall outside a certain threshold (e.g., more than 3 standard deviations away). Another method is the interquartile range (IQR), where data points outside the range of 1.5 times the IQR are considered outliers.

3. Domain Knowledge: Leverage your domain expertise to identify potential outliers. If you have a good understanding of the data and the context in which it was collected, you may be able to identify values that are implausible or inconsistent with what is expected.

4. Machine Learning Techniques: You can use machine learning algorithms to detect outliers. Unsupervised learning algorithms like clustering or density-based methods (e.g., DBSCAN) can help identify unusual patterns or clusters in the data that may indicate outliers.

5. Data Validation: Cross-check your data with external sources or known benchmarks. If possible, compare your data with other reliable sources or conduct external validation to verify its accuracy and consistency.

6. Outlier Detection Models: Train outlier detection models on your dataset. These models can learn patterns from the majority of the data and flag any observations that deviate significantly from those patterns.

It's important to note that not all outliers are necessarily liars or errors; some may represent valid and interesting data points. It's crucial to carefully investigate and understand the reasons behind the outliers before making any decisions about their treatment or exclusion from the analysis.



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Nvidia has launched multiple GenAi, and AI courses.

Check this video!

https://www.instagram.com/reel/C7hAmjyPGPc/?igsh=YzFxaTAxcTV0M2tw

FREE COURSES link:- 🖇️
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Walmart global is hiring for Data Analyst role

0-2 years of experience is required

So any fresher can apply

https://www.linkedin.com/jobs/view/3849477026

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Barclays is hiring for a fresher entry level data analyst!
https://search.jobs.barclays/job/-/-/13015/65691977856?src=JB-12860&

Hi all,
I have updated the SQL roadmap with the 🔗 links .



Here's the link.

https://docs.google.com/document/d/1rk7A5vqLXRhrTwIgHcnxL15JxMWwsvqsj7PlWZL0Ufk/edit?usp=drivesdk

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👉👉Here's how you can create a portfolio using python.

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Swiss Re is hiring!
Position: Associate Data Analyst
Qualification: Bachelor’s/ Master’s Degree
Salary: 8 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore, India

📌Apply Now: https://careers.swissre.com/job/Bangalore-Associate-Data-Analyst-KA/1065982501/

Grow Solutions Hiring for Fresher Data Analyst              
Location: Gujrat
Qualification : Any degree       
Work Experience: Fresher        
CTC: upto 8 LPA                 
Apply Link: https://grow.keka.com/careers/jobdetails/59500


Deliveroo Hiring for Fresher Machine Learning Engineer          
Location: Hyderabad
Qualification : Any degree       
Work Experience: Fresher        
CTC: upto 8 LPA                 
Apply Link: https://boards.greenhouse.io/deliveroo/jobs/5688028?gh_src=1df4cbd01us

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Natwest Group is hiring for the role of Business Analyst.

Experince - 1 to 3 Years
Location - Chennai

Apply Link -
https://unstop.com/o/KziQcS9?lb=8eEx09ow&utm_medium=Share&utm_source=shortUrl

Free courses/Tutorials for learning.


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