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๐Ÿฑ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ฌ๐—ผ๐˜‚ ๐—–๐—ฎ๐—ปโ€™๐˜ ๐— ๐—ถ๐˜€๐˜€๐Ÿ˜

Microsoft Learn is offering 5 must-do courses for aspiring data scientists, absolutely free๐Ÿ”ฅ๐Ÿ“Š

These self-paced learning modules are designed by industry experts and cover everything from Python and ML to Microsoft Fabric and Azure๐ŸŽฏ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4iSWjaP

Job-ready content that gets you resultsโœ…๏ธ
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How to enter into Data Science

๐Ÿ‘‰Start with the basics: Learn programming languages like Python and R to master data analysis and machine learning techniques. Familiarize yourself with tools such as TensorFlow, sci-kit-learn, and Tableau to build a strong foundation.

๐Ÿ‘‰Choose your target field: From healthcare to finance, marketing, and more, data scientists play a pivotal role in extracting valuable insights from data. You should choose which field you want to become a data scientist in and start learning more about it.

๐Ÿ‘‰Build a portfolio: Start building small projects and add them to your portfolio. This will help you build credibility and showcase your skills.
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Forwarded from Artificial Intelligence
๐—•๐—ผ๐—ผ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€ ๐˜„๐—ถ๐˜๐—ต ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€๐Ÿ˜

Ready to take your career to the next level?๐Ÿ“Š๐Ÿ“Œ

These free certification courses offer a golden opportunity to build expertise in tech, programming, AI, and moreโ€”all for free!๐Ÿ”ฅ๐Ÿ’ป

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These courses are your stepping stones to successโœ…๏ธ
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9 tips to learn programming faster:

Build small projects from day 1

Donโ€™t memorize, understand the logic

Learn by debugging your own code

Google is your best friend

Break big problems into chunks

Teach others what youโ€™ve learned

Be consistent โ€” code daily

Read others' code on GitHub

Donโ€™t rush โ€” master the basics

Free Programming Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17

ENJOY LEARNING ๐Ÿ‘๐Ÿ‘
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๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ฉ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ป๐˜€๐—ต๐—ถ๐—ฝ ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐˜€ ๐—œ๐—ป ๐—ง๐—ผ๐—ฝ ๐—–๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€๐Ÿ˜

1๏ธโƒฃ BCG Data Science & Analytics Virtual Experience
2๏ธโƒฃ TATA Data Visualization Internship
3๏ธโƒฃ Accenture Data Analytics Virtual Internship

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/409RHXN

Enroll for FREE & Get Certified ๐ŸŽ“
Prompt Engineer vs Data Scientist ๐Ÿ˜…
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๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐Ÿญ๐Ÿฌ๐Ÿฌ% ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—”๐˜‡๐˜‚๐—ฟ๐—ฒ, ๐—”๐—œ, ๐—–๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† & ๐— ๐—ผ๐—ฟ๐—ฒ๐Ÿ˜

Want to upskill in Azure, AI, Cybersecurity, or App Developmentโ€”without spending a single rupee?๐Ÿ‘จโ€๐Ÿ’ป๐ŸŽฏ

Enter Microsoft Learn โ€” a 100% free platform that offers expert-led learning paths to help you grow๐Ÿ“Š๐Ÿ“Œ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

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Enjoy Learning โœ…๏ธ
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Hyperparameter tuning is the process of selecting the optimal set of hyperparameters for a machine learning model to improve its performance. Hyperparameters are parameters that are set before the learning process begins and control the learning process itself, such as the learning rate, number of hidden layers in a neural network, or the depth of a decision tree.

Here is how hyperparameter tuning works:

1. Define Hyperparameters: The first step is to define the hyperparameters that need to be tuned. These are typically specified before training the model and can significantly impact the model's performance.

2. Choose a Search Space: Next, a search space is defined for each hyperparameter, which includes the range of values or options that will be explored during the tuning process. This can be done manually or using automated tools like grid search, random search, or Bayesian optimization.

3. Evaluation Metric: An evaluation metric is selected to measure the performance of the model with different hyperparameter configurations. Common metrics include accuracy, precision, recall, F1 score, or area under the curve (AUC).

4. Hyperparameter Optimization: The hyperparameter tuning process involves training multiple models with different hyperparameter configurations and evaluating their performance using the chosen evaluation metric. This process continues until the best set of hyperparameters that optimize the model's performance is found.

5. Cross-Validation: To ensure the robustness of the hyperparameter tuning process and avoid overfitting, cross-validation is often used. The dataset is split into multiple folds, and each fold is used for training and validation to assess the model's generalization performance.

6. Model Selection: Once the hyperparameter tuning process is complete, the model with the best hyperparameter configuration based on the evaluation metric is selected as the final model.

Hyperparameter tuning is a crucial step in machine learning model development as it can significantly impact the model's accuracy, generalization ability, and overall performance. By systematically exploring different hyperparameter configurations, data scientists can fine-tune their models to achieve optimal results for specific tasks and datasets.

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

Credits: https://t.iss.one/datasciencefun

Like if you need similar content ๐Ÿ˜„๐Ÿ‘

Hope this helps you ๐Ÿ˜Š
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๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐— ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ฒ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—ณ๐—ฟ๐—ผ๐—บ ๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ ๐—˜๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟ๐˜€ โ€” ๐—™๐—ผ๐—ฟ ๐—™๐—ฟ๐—ฒ๐—ฒ!๐Ÿ˜

Want to break into machine learning but not sure where to start?๐Ÿ’ป

Googleโ€™s Machine Learning Crash Course is the perfect launchpadโ€”absolutely free, beginner-friendly, and created by the engineers behind the tools.๐Ÿ‘จโ€๐Ÿ’ป๐Ÿ“Œ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4jEiJOe

All The Best ๐ŸŽŠ
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Forwarded from Artificial Intelligence
๐—™๐—ฅ๐—˜๐—˜ ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜

Feeling like your resume could use a boost? ๐Ÿš€

Letโ€™s make that happen with Microsoft Azure certifications that are not only perfect for beginners but also completely free!๐Ÿ”ฅ๐Ÿ’ฏ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

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Essential skills for todayโ€™s tech-driven worldโœ…๏ธ
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Steps to become data analyst when you are fresher ๐Ÿ‘‡๐Ÿ‘‡

1 - First try to focus 3 mandatory skills i.e. Sql, Ms excel and python -

- For sql you can refer Ankit Bansal Or Thoufiq Mohammed (techtfq) on @sqlanalyst
- For Ms excel refer Leila Gharani or @excel_analyst
- For python refer freecodecamp from YouTube or @pythonanalyst

2 - After that try to be clear with basic idea of tableau or powerbi. (Not mandatory for every job). You can refer this channel for free resources https://t.iss.one/PowerBI_analyst

3 - Add your college project in your resume, if it's a data science related project it will help a lot. If you don't have project then you can make some dashboarding projects from YouTube in tableau/powerbi.

4 - And start applying for jobs which is having 0-1 yr experience required, you can also apply for 1 yr experience required job in analytics because sometimes they may consider fresher also. You can refer this channel @jobs_sql for job opportunities
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๐—ง๐—ผ๐—ฝ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ณ๐—ผ๐—ฟ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ โ€” ๐—ฅ๐—ฒ๐—ฐ๐—ฒ๐—ป๐˜๐—น๐˜† ๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ฏ๐˜† ๐— ๐—ก๐—–๐˜€๐Ÿ˜

๐Ÿ“Œ Preparing for Python Interviews in 2025?๐Ÿ—ฃ

If youโ€™re aiming for roles in data analysis, backend development, or automation, Python is your key weaponโ€”and so is preparing with the right questions.๐Ÿ’ปโœจ๏ธ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/3ZbAtrW

Crack your next Python interviewโœ…๏ธ
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