👨‍💻 𝟓 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐤𝐢𝐥𝐥𝐬 𝐄𝐯𝐞𝐫𝐲 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 𝐍𝐞𝐞𝐝𝐬 𝐢𝐧 𝐚𝐧 𝐎𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 📊

🔸𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 & 𝐔𝐧𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
You need to understand two main types of machine learning: supervised learning (used for predicting outcomes, like whether a customer will buy a product) and unsupervised learning (used to find patterns, like grouping customers based on buying behavior).

🔸𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠
This is about turning raw data into useful information for your model. Knowing how to clean data, fill missing values, and create new features will improve the model's performance.

🔸𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐧𝐠 𝐌𝐨𝐝𝐞𝐥𝐬
It’s important to know how to check if a model is working well. Use simple measures like accuracy (how often the model is right), precision, and recall to assess your model’s performance.

🔸𝐅𝐚𝐦𝐢𝐥𝐢𝐚𝐫𝐢𝐭𝐲 𝐰𝐢𝐭𝐡 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬
Get to know basic machine learning algorithms like Decision Trees, Random Forests, and K-Nearest Neighbors (KNN). These are often used for solving real-world problems and can help you choose the best approach.

🔸𝐃𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐌𝐨𝐝𝐞𝐥𝐬
Once you’ve built a model, it’s important to know how to use it in the real world. Learn how to deploy models so they can be used by others in your organization and continue to make decisions automatically.

🔍 𝐏𝐫𝐨 𝐓𝐢𝐩: Keep practicing by working on real projects or using online platforms to improve these skills!

Data Science & Machine Learning Resources: https://topmate.io/coding/914624

Like if you need similar content 😄👍

Hope this helps you 😊

#ai #datascience

Microsoft hiring for freshers Applied Science Intern!!

https://jobs.careers.microsoft.com/global/en/job/1801106/Applied-Sciences-Intern

👉WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

👉Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5

Like for more ❤️

All the best 👍 👍

Reflecting on a memorable interview experience with Kotak Mahindra Bank for the SDE-2 (Data Engineering) role! 🌟 It comprised four stimulating rounds, featuring two bar raiser and two internal rounds.

Round 1: Delved deep into DS & Algo, SQL data modeling, and Data Warehousing, setting the stage for a robust discussion.

Round 2: Focused on Pipeline designing and Spark, challenging me to showcase my skills in designing efficient data pipelines.

Round 3: Dived into SQL and Spark optimization, where I had the opportunity to demonstrate my expertise in enhancing performance.

Round 4: A dynamic mix of everything, including streaming and writing ETL for various scenarios, truly putting my skills to the test.

Prepare for GATE: The Right Time is NOW!

GeeksforGeeks brings you everything you need to crack GATE 2026 – 900+ live hours, 300+ recorded sessions, and expert mentorship to keep you on track.

What’s inside?

✔ Live & recorded classes with India’s top educators
✔ 200+ mock tests to track your progress
✔ Study materials - PYQs, workbooks, formula book & more
✔ 1:1 mentorship & AI doubt resolution for instant support
✔ Interview prep for IITs & PSUs to help you land opportunities

Learn from Experts Like:

Satish Kumar Yadav – Trained 20K+ students
Dr. Khaleel – Ph.D. in CS, 29+ years of experience
Chandan Jha – Ex-ISRO, AIR 23 in GATE
Vijay Kumar Agarwal – M.Tech (NIT), 13+ years of experience
Sakshi Singhal – IIT Roorkee, AIR 56 CSIR-NET
Shailendra Singh – GATE 99.24 percentile
Devasane Mallesham – IIT Bombay, 13+ years of experience

Use code UPSKILL30 to get an extra 30% OFF (Limited time only)

📌 Enroll for a free counseling session now: https://gfgcdn.com/tu/UI2/

Any person learning deep learning or artificial intelligence in particular, know that there are ultimately two paths that they can go:

1. Computer vision
2. Natural language processing.

I outlined a roadmap for computer vision I believe many beginners will find helpful.

Artificial Intelligence 👇👇

1. What are the uses of using RNN in NLP?

The RNN is a stateful neural network, which means that it not only retains information from the previous layer but also from the previous pass. Thus, this neuron is said to have connections between passes, and through time.
For the RNN the order of the input matters due to being stateful. The same words with different orders will yield different outputs.
RNN can be used for unsegmented, connected applications such as handwriting recognition or speech recognition.

2. How to remove values to a python array?

Ans: Array elements can be removed using pop() or remove() method. The difference between these two functions is that the former returns the deleted value whereas the latter does not.

3. What are the advantages and disadvantages of views in the database?

Answer: Advantages of Views:
As there is no physical location where the data in the view is stored, it generates output without wasting resources.
Data access is restricted as it does not allow commands like insertion, updation, and deletion.
Disadvantages of Views:
The view becomes irrelevant if we drop a table related to that view.
Much memory space is occupied when the view is created for large tables.

4. Describe the Difference Between Window Functions and Aggregate Functions in SQL.

The main difference between window functions and aggregate functions is that aggregate functions group multiple rows into a single result row; all the individual rows in the group are collapsed and their individual data is not shown. On the other hand, window functions produce a result for each individual row. This result is usually shown as a new column value in every row within the window.

5. What is Ribbon in Excel and where does it appear?

The Ribbon is basically your key interface with Excel and it appears at the top of the Excel window. It allows users to access many of the most important commands directly. It consists of many tabs such as File, Home, View, Insert, etc. You can also customize the ribbon to suit your preferences. To customize the Ribbon, right-click on it and select the “Customize the Ribbon” option.

SQL Complete Handwritten Notes🗒

React ❤️ for more

NatWest Group is hiring Data & Analytics Analyst

https://jobs.natwestgroup.com/jobs/15775632-data-and-analytics-analyst?bid=370

https://jobs.natwestgroup.com/jobs/15775631-data-and-analytics-analyst?bid=370

Zeta is hiring Data Science Intern 🚀

Qualification: Bachelor's degree in Engineering
Location: Bangalore

Apply link : https://jobs.lever.co/zeta/213ee609-8204-4093-b20c-4517526e7838/apply?source=LinkedIn

👉WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

👉Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5

Like for more ❤️

All the best 👍 👍

Swiggy hiring Senior Data Scientist

https://careers.swiggy.com/#/careers?p=eyJwYWdlVHlwZSI6ImpkIiwiY3ZTb3VyY2UiOiJsaW5rZWRpbiIsInJlcUlkIjoxODMyOCwicmVxdWVzdGVyIjp7ImlkIjoiIiwiY29kZSI6IiIsIm5hbWUiOiIifSwicGFnZSI6ImNhcmVlcnMiLCJidWZpbHRlciI6LTF9

Let’s go back to the basics...!

Here’s what you do to become a Data Analyst

- Learn SQL (best skill to have)
- Learn Excel (hidden requirement)
- Learn a BI tool (for nice portfolio projects)

Don’t stop there you still have work to do

- Create a portfolio
- Learn how to create an appealing resume
- Learn how to answer interview questions (STAR method)

After this, my favorite, networking

- Comment on posts
- Start posting yourself
- Reach out to all the recruiters

It can take you anywhere from a couple of months to a year!

It all depends on how much time you can dedicate each day!

But the longer you wait, the longer it will take!

Get after it...!

CoinDCX is hiring for Data Engineer

Experience: 1 year
Expected Salary: 20-40 LPA

Apply here: https://careers.coindcx.com/opportunities/jd?p=eyJwYWdlVHlwZSI6ImpkIiwiY3ZTb3VyY2UiOiJsaW5rZWRpbiIsInJlcUlkIjoxMDU4LCJyZXF1ZXN0ZXIiOnsiaWQiOiIiLCJjb2RlIjoiIiwibmFtZSI6IiJ9LCJwYWdlIjoiY2FyZWVycyIsImJ1ZmlsdGVyIjotMX0%3D


AssetIntel is hiring for Frontend Engineer (Remote)

Experience: 3 year's
Expected Salary: 10-30 LPA

Apply here: https://wellfound.com/jobs/3246774-frontend-engineer-remote-india


Revvity is hiring for Intern

Experience: 0 - 2 year's
Expected Stipend: 4-7 LPA

Apply here: https://jobs.revvity.com/en/job/-/-/20539/78981709968

📌Company Name: Zeta
Role: Data Science Intern

Qualification: Bachelor's degree in engineering

💻Apply Link: https://jobs.lever.co/zeta/213ee609-8204-4093-b20c-4517526e7838/

We Are Hiring- Gen AI Engineer- Remote
🚀 General AI Engineer - 2+ Years Experience in AI/ML (1+ Years in Gen AI)
As a General AI Engineer, you will play a crucial role in developing, implementing, and maintaining advanced AI systems that drive innovation and solve complex problems. You'll collaborate with cross-functional teams to design and deploy AI solutions that enhance products and services, pushing the boundaries of what AI can achieve. 🌐
Key Responsibilities:
Collaborate with cross-functional teams to design and deploy AI solutions 🤝
Develop and maintain advanced AI systems 💡
Implement innovative solutions in generative AI 🤖
Skill Set:
🖥️ Expertise in Python, Data Structures, and API Calls - Strong foundation for working with generative AI models and frameworks.
🗣️ Strong Communication Skills (Documentation & Presentations) - Ability to clearly document and present complex technical concepts for both technical and non-technical audiences.
🤝 Effective Teamwork and Solo Work - Collaborate on large projects while also driving research and development independently.
🔍 Data Mining and Text Processing - Extract valuable insights from various data sources to train and improve generative models.
⚙️ Building RAG Pipelines (Highly Desired) - Experience building retrieval-augmented generation pipelines for generative AI.
💻 Machine Learning (ML), NLP, GANs, Transformers & BERT - Solid understanding of core generative AI concepts.
🛠️ Hands-on Experience with Vector Databases - Experience with Chroma DB, PineCone, Milvus, FAISS, Arango DB for data storage and retrieval.
🤝 Collaboration - Work closely with Business Analysts (BAs), Development Teams, and DevOps teams to bring AI solutions to life.
📱 Embedded Models - Familiarity with deploying generative models on resource-constrained devices (e.g., Open AI – Ada Embedding 002 model).
⚡ Experience with POC Tools (Streamlit, Gradio) - Prototype and showcase generative AI concepts quickly.
☁️ Cloud Experience (AWS Bedrock or similar) - Expertise in deploying large-scale generative AI models on cloud platforms (e.g., EC2, ECS, S3, SageMaker).
🔍 Expertise in LLMs - In-depth knowledge of a specific LLM (e.g., OpenAI, Jurassic-1 Jumbo, LLAMA, Mistral, Mixtral, Gemini Pro).
Interested?
Please share your resume to karthicc@nallas.com 📧

🔰 140+ Basic to Advanced Python Tutorial Full pdf 📝

React ❤️ for more 📱

🚀 MongoDB is Hiring – Senior Business Systems Analyst

Req ID - 1263096719

Gurugram, Haryana, India 🌟


Join team at MongoDB as we redefine CRM excellence!
This role can be based in our Gurgaon office or remotely across India.
📌 What You’ll Do:
✅ Be a Salesforce expert (Sales Cloud, Forecasting, Deal Management)
✅ Analyze user journeys & optimize processes
✅ Build scalable, cross-functional solutions
✅ Collaborate with teams like Sales, Finance & more
🎯 What We’re Looking For:
💻 Expertise in Salesforce configuration (flows, automation, reports)
🔍 Strong analytical and problem-solving skills
⚡ Agile mindset with a focus on continuous improvement

📧 Interested?
https://www.mongodb.com/careers/jobs/6707614

Some useful telegram channels to learn data analytics & data science

Python interview books
👇👇
https://t.me/dsabooks

Data Analyst Interviews
👇👇
https://t.me/DataAnalystInterview

SQL for data analysis
👇👇
https://t.me/sqlanalyst

Data Science &  Machine Learning
👇👇
https://t.me/datasciencefun

Data Science Projects
👇👇
https://t.me/pythonspecialist

Python for data analysis
👇👇
https://t.me/pythonanalyst

Excel for data analysis
👇👇
https://t.me/excel_analyst

Power BI/ Tableau
👇👇
https://t.me/PowerBI_analyst

Data Analysis Books
👇👇
https://t.me/learndataanalysis

Gartner is hiring Data Analyst 🚀

Experience : 0-3 Years
Location : Bangalore

Apply link : https://gartner.wd5.myworkdayjobs.com/EXT/job/Gurgaon/Data-Analyst-Associate-Data-Analyst_94692-1/apply?source=JB-10120

Insta Astro is hiring Product Analyst 🚀

Experience : 0-1 Years
Location : Noida

Apply link : Check out this job at InstaAstro: https://www.linkedin.com/jobs/view/4191533201

Creating a data science portfolio is a great way to showcase your skills and experience to potential employers. Here are some steps to help you create a strong data science portfolio:

1. Choose relevant projects: Select a few data science projects that demonstrate your skills and interests. These projects can be from your previous work experience, personal projects, or online competitions.

2. Clean and organize your code: Make sure your code is well-documented, organized, and easy to understand. Use comments to explain your thought process and the steps you took in your analysis.

3. Include a variety of projects: Try to include a mix of projects that showcase different aspects of data science, such as data cleaning, exploratory data analysis, machine learning, and data visualization.

4. Create visualizations: Data visualizations can help make your portfolio more engaging and easier to understand. Use tools like Matplotlib, Seaborn, or Tableau to create visually appealing charts and graphs.

5. Write project summaries: For each project, provide a brief summary of the problem you were trying to solve, the dataset you used, the methods you applied, and the results you obtained. Include any insights or recommendations that came out of your analysis.

6. Showcase your technical skills: Highlight the programming languages, libraries, and tools you used in each project. Mention any specific techniques or algorithms you implemented.

7. Link to your code and data: Provide links to your code repositories (e.g., GitHub) and any datasets you used in your projects. This allows potential employers to review your work in more detail.

8. Keep it updated: Regularly update your portfolio with new projects and skills as you gain more experience in data science. This will show that you are actively engaged in the field and continuously improving your skills.

By following these steps, you can create a comprehensive and visually appealing data science portfolio that will impress potential employers and help you stand out in the competitive job market.