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Perfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence Admin: @coderfun
Show moreπ Analytical overview of Telegram channel Machine Learning & Artificial Intelligence | Data Science Free Courses
Channel Machine Learning & Artificial Intelligence | Data Science Free Courses (@datasciencefree) in the English language segment is an active participant. Currently, the community unites 66 858 subscribers, ranking 2 451 in the Education category and 428 in the Malaysia region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 66 858 subscribers.
According to the latest data from 29 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 462 over the last 30 days and by 17 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 0.65%. Within the first 24 hours after publication, content typically collects 1.31% reactions from the total number of subscribers.
- Post reach: On average, each post receives 437 views. Within the first day, a publication typically gains 872 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 sellerflash, waybienad, pricing, buybox, buyer.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βPerfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence
Admin: @coderfunβ
Thanks to the high frequency of updates (latest data received on 30 June, 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.
66 858
Subscribers
+1724 hours
+1507 days
+46230 days
Posts Archive
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Repost from Data Science & Machine Learning
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Python for Data Science -1.pdf7.57 MB
Large English learning resources collection
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Preparing for a data science interview can be challenging, but with the right approach, you can increase your chances of success. Here are some tips to help you prepare for your next data science interview:
π 1. Review the Fundamentals: Make sure you have a thorough understanding of the fundamentals of statistics, probability, and linear algebra. You should also be familiar with data structures, algorithms, and programming languages like Python, R, and SQL.
π 2. Brush up on Machine Learning: Machine learning is a key aspect of data science. Make sure you have a solid understanding of different types of machine learning algorithms like supervised, unsupervised, and reinforcement learning.
π 3. Practice Coding: Practice coding questions related to data structures, algorithms, and data science problems. You can use online resources like HackerRank, LeetCode, and Kaggle to practice.
π 4. Build a Portfolio: Create a portfolio of projects that demonstrate your data science skills. This can include data cleaning, data wrangling, exploratory data analysis, and machine learning projects.
π 5. Practice Communication: Data scientists are expected to effectively communicate complex technical concepts to non-technical stakeholders. Practice explaining your projects and technical concepts in simple terms.
π 6. Research the Company: Research the company you are interviewing with and their industry. Understand how they use data and what data science problems they are trying to solve.
By following these tips, you can be well-prepared for your next data science interview. Good luck!
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Practical Implementation of a Data Lake
Nayanjyoti Paul, 2023
Machine Learning with Python -> Amin Zollanvari
If you want to learn about crypto currency & Bitcoin, here is the perfect resource for you
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Modern Computer Vision with Pytorch
V. Kishore Ayyadevara, 2020
What if we all are just a part of AI experiment by god- humanβs life created as a unique dataset, contributing to the overall learning process. The Creator, observes the intricate patterns emerging from the myriad interactions among the humans.
Read more.....
BCG Hiring ML Engineer
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https://t.me/getjobss/1851
Requirements:
Very high proficiency in Python programming language, knowledge of other languages.
such as R, Java would be a plus.
Knowledge of various AI/ML models including deep learning models.
Knowledge of Generative AI stack β Large Language Models / Foundation Models, vector databases, orchestration stack.
Hand on experience in building AI orchestration with frameworks like LangChain.
Knowledge of vector databases e.g., Pinecone, Chroma etc.
Deep understanding of data processing frameworks e.g., Data Bricks, Airflow etc.
Knowledge of API frameworks Django, Flask etc.
Understanding of cloud data & AI stack on AWS / Azure / GCP is preferred.
ENJOY LEARNING ππ
Statistics For Data Science !.pdf1.29 MB
Famous ML Project Ideas
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https://t.me/pythonspecialist/103
