اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Artificial Intelligence
رفتن به کانال در Telegram
🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data
نمایش بیشتر📈 تحلیل کانال تلگرام Artificial Intelligence
کانال Artificial Intelligence (@machinelearning_deeplearning) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 53 161 مشترک است و جایگاه 3 256 را در دسته آموزش و رتبه 7 041 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 53 161 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 09 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 1 045 و در ۲۴ ساعت گذشته برابر 38 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 5.69% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.68% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 3 022 بازدید دریافت میکند. در اولین روز معمولاً 892 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 9 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند learning, classification, layer, pattern, chatbot تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“🔰 Machine Learning & Artificial Intelligence Free Resources
🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more
For Promotions: @love_data”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 10 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کردهاند.
53 161
مشترکین
+3824 ساعت
+1977 روز
+1 04530 روز
آرشیو پست ها
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8 FREE AI Courses by Google 🎓🚀 Learn, Grow, and Succeed
1. Introduction to Generative AI
→ An introductory course to explain what generative AI is.
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→ Discover how to train and deploy a model to generate images.
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→ Integrate AI into your apps.
→ Find out about Generative AI Studio, what it can do, and it's features.
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8. Image recognition
→ Learn how to create an AI that understands images.
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All the best 👍👍
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𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽𝘀 𝗧𝗼 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲😍
1️⃣ BCG Data Science & Analytics
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𝐋𝐢𝐧𝐤 👇:-
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𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
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These free full courses will take you from beginner to expert!
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Underrated Telegram Channel for Data Analysts 👇👇
https://t.me/sqlspecialist
Here, you will get free tutorials to learn SQL, Python, Power BI, Excel and many more
Hope you guys will like it 😄
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To automate your daily tasks using ChatGPT, you can follow these steps:
1. Identify Repetitive Tasks: Make a list of tasks that you perform regularly and that can potentially be automated.
2. Create ChatGPT Scripts: Use ChatGPT to create scripts or workflows for automating these tasks. You can use the API to interact with ChatGPT programmatically.
3. Integrate with Other Tools: Integrate ChatGPT with other tools and services that you use to streamline your workflow. For example, you can connect ChatGPT with task management tools, calendar apps, or communication platforms.
4. Set up Triggers: Set up triggers that will initiate the automated tasks based on certain conditions or events. This could be a specific time of day, a keyword in a message, or any other criteria you define.
5. Test and Iterate: Test your automated workflows to ensure they work as expected. Make adjustments as needed to improve efficiency and accuracy.
6. Monitor Performance: Keep an eye on how well your automated tasks are performing and make adjustments as necessary to optimize their efficiency.
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𝗠𝗮𝘀𝘁𝗲𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗧𝗵𝗲𝘀𝗲 𝗙𝗥𝗘𝗘 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗩𝗶𝗱𝗲𝗼𝘀!😍
Want to become a Data Analytics pro?🔥
These tutorials simplify complex topics into easy-to-follow lessons✨️
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+3
🔗 Master 8 Essential Machine Learning Algorithms
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𝗠𝗮𝘀𝘁𝗲𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻 – 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲!😍
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🚀 Here’s your step-by-step guide! From simple coding to hands-on projects and expert topics.
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Essential Data Analysis Techniques Every Analyst Should Know
1. Descriptive Statistics: Understanding measures of central tendency (mean, median, mode) and measures of spread (variance, standard deviation) to summarize data.
2. Data Cleaning: Techniques to handle missing values, outliers, and inconsistencies in data, ensuring that the data is accurate and reliable for analysis.
3. Exploratory Data Analysis (EDA): Using visualization tools like histograms, scatter plots, and box plots to uncover patterns, trends, and relationships in the data.
4. Hypothesis Testing: The process of making inferences about a population based on sample data, including understanding p-values, confidence intervals, and statistical significance.
5. Correlation and Regression Analysis: Techniques to measure the strength of relationships between variables and predict future outcomes based on existing data.
6. Time Series Analysis: Analyzing data collected over time to identify trends, seasonality, and cyclical patterns for forecasting purposes.
7. Clustering: Grouping similar data points together based on characteristics, useful in customer segmentation and market analysis.
8. Dimensionality Reduction: Techniques like PCA (Principal Component Analysis) to reduce the number of variables in a dataset while preserving as much information as possible.
9. ANOVA (Analysis of Variance): A statistical method used to compare the means of three or more samples, determining if at least one mean is different.
10. Machine Learning Integration: Applying machine learning algorithms to enhance data analysis, enabling predictions, and automation of tasks.
Like this post if you need more 👍❤️
Hope it helps :)
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𝗙𝗥𝗘𝗘 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
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"I am an AI Tools & ChatGPT Expert, and my salary package is 42 LPA."
Sounds familiar? If you’ve been on YouTube recently, I’m sure you’ve seen this ad at least 100 times. Now, I have just one simple question – Can someone please tell me which companies are hiring for this role and paying 42 LPA? Because I’m also considering a career switch! 😂
See guys, learning how to use a few AI tools won't magically get you a 42 LPA job. Selling courses isn’t wrong, but selling them by giving false hopes is. Just because someone tells you that learning how to use a few AI tools will instantly land you a high-paying job doesn’t make it true.
So, a humble request – don’t fall for these unrealistic promises. Invest in courses only to upskill yourself, not with the expectation of overnight success.
If anyone actually finds this 42 LPA AI Tools & ChatGPT Expert job, please let me know. I’ll also update my resume! 🤣
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Master AI in 2025 – A Quick Roadmap 🚀
AI can be overwhelming, but following a structured path makes it easier. Here’s the roadmap:
1. Build Strong Foundations Learn Python, data structures, linear algebra, statistics & version control before diving into AI.
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5. Choose an AI Specialization Focus on NLP, computer vision, reinforcement learning, or AI in business and healthcare.
6. Learn Large Language Models (LLMs) Work with GPT, LLaMA, fine-tuning, Retrieval-Augmented Generation (RAG), and AI APIs.
7. Master AI Deployment & MLOps Deploy models using Flask, FastAPI, Docker, Kubernetes, and automate pipelines.
