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Data Science & Machine Learning

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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data

Network: Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT ExpertIndia3 828Education2 011...

📈 Analytical overview of Telegram channel Data Science & Machine Learning

Channel Data Science & Machine Learning (@datasciencefun) in the English language segment is an active participant. Currently, the community unites 77 694 subscribers, ranking 2 011 in the Education category and 3 828 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 77 694 subscribers.

According to the latest data from 10 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -93 over the last 30 days and by -5 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 3.28%. Within the first 24 hours after publication, content typically collects 0.99% reactions from the total number of subscribers.
Post reach: On average, each post receives 2 549 views. Within the first day, a publication typically gains 767 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
Thematic interests: Content is focused on key topics such as learning, accuracy, distribution, panda, dataset.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data”

Thanks to the high frequency of updates (latest data received on 11 November, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

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77 694

Subscribers

-524 hours

-377 days

-9330 days

2 549

Post views

~ 76724 hours

~ 1 03648 hours

3.28%

Engagement rate

~ 1

Posts per day

Ads index

Posts Archive

77 694

Statistics 101.pdf7.57 MB

77 694

alex-galea-the-applied-data-science-workshop-second.pdf12.10 MB

77 694

💎 Wanna join the crypto elite? Khalifa Trades, the renowned millionaire, raked in a staggering $5 million in profits last year. Now, he's making Dubai his home, and he's ready to share his priceless knowledge with you. No ads, no gimmicks. Pure profit-making. Join now! 👉 https://t.me/+721w0zDG7ntjNWI0

77 694

🔰 Python for Machine Learning & Data Science Masterclass 👇👇 https://t.me/datasciencefree/2

77 694

Data Science Bookcamp (2021).pdf42.41 MB

77 694

A Hands-On Introduction to Data Science Chirag Shah, 2020

77 694

Building IoT Visualizations using Grafana Rodrigo Juan Hernandez, 2022

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Statistical Mechanics of Neural Networks ( Haiping Huang ). Springer 2021

77 694

Netflix ML Architecture

77 694

Repost from Python Projects & Resources

Advanced Python: Practical Database Examples.zip253.86 MB

77 694

100 Data Structure interview Question & Answers .pdf8.07 KB

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Finland is a country with the fascinating nature, clean ecology and high living standards. It is a great place to grow children! We invite you to learn more about this wonderful country and join us for a free webinar “Relocation to Finland for Tech Specialists” June, 6 at 19:00, India Standard Time Online We’ll talk about: 1. What kind of Tech Talents are in demand in Finland? 2. Salary ranges and taxes 3. Family living costs 4. And what is the most important - how to succeed in job searching and easily pass interviews 500+ Tech Talents from various countries have moved to Finland in 2022 with our support, so can you! Try your hand! Join the channel and turn on notifications to get the link to the upcoming webinar: https://t.me/nerdsbay

77 694

Overview of Machine Learning

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deep-learning-for-computer-architects.pdf2.77 MB

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🖥 Free Courses on Large Language Models ▪ChatGPT Prompt Engineering for Developers ▪LangChain for LLM Application Development ▪Building Systems with the ChatGPT API ▪Google Cloud Generative AI Learning Path ▪Introduction to Large Language Models with Google Cloud ▪LLM University ▪Full Stack LLM Bootcamp

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Python Notes 👇 https://t.me/pythondevelopersindia/576

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1. Can you explain how the memory cell in an LSTM is implemented computationally? The memory cell in an LSTM is implemented as a forget gate, an input gate, and an output gate. The forget gate controls how much information from the previous cell state is forgotten. The input gate controls how much new information from the current input is allowed into the cell state. The output gate controls how much information from the cell state is allowed to pass out to the next cell state. 2. What is CTE in SQL? A CTE (Common Table Expression) is a one-time result set that only exists for the duration of the query. It allows us to refer to data within a single SELECT, INSERT, UPDATE, DELETE, CREATE VIEW, or MERGE statement's execution scope. It is temporary because its result cannot be stored anywhere and will be lost as soon as a query's execution is completed. 3. List the advantages NumPy Arrays have over Python lists? Python’s lists, even though hugely efficient containers capable of a number of functions, have several limitations when compared to NumPy arrays. It is not possible to perform vectorised operations which includes element-wise addition and multiplication. They also require that Python store the type information of every element since they support objects of different types. This means a type dispatching code must be executed each time an operation on an element is done. 4. What’s the F1 score? How would you use it? The F1 score is a measure of a model’s performance. It is a weighted average of the precision and recall of a model, with results tending to 1 being the best, and those tending to 0 being the worst. 5. Name an example where ensemble techniques might be useful? Ensemble techniques use a combination of learning algorithms to optimize better predictive performance. They typically reduce overfitting in models and make the model more robust (unlikely to be influenced by small changes in the training data). You could list some examples of ensemble methods (bagging, boosting, the “bucket of models” method) and demonstrate how they could increase predictive power.

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machine-learning-yearning-draft-version.pdf4.01 MB

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Data Science With Python Workflow Cheat Sheet Creator: business Science Stars ⭐️: 75 Forked By: 38 https://github.com/business-science/cheatsheets/blob/master/Data_Science_With_Python_Workflow.pdf