Artificial Intelligence

Kanalga Telegram’da o‘tish

🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data

Ko'proq ko'rsatish

Tarmoq:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert Hindiston7 041 Taʼlim3 256...

📈 Telegram kanali Artificial Intelligence analitikasi

Artificial Intelligence (@machinelearning_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 53 161 obunachidan iborat bo'lib, Taʼlim toifasida 3 256-o'rinni va Hindiston mintaqasida 7 041-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 53 161 obunachiga ega bo‘ldi.

09 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 1 045 ga, so‘nggi 24 soatda esa 38 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 5.69% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.68% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 3 022 marta ko‘riladi; birinchi sutkada odatda 892 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 9 ta reaksiya keladi.
Tematik yo‘nalishlar: Kontent learning, classification, layer, pattern, chatbot kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 10 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

53 161

Obunachilar

+3824 soatlar

+1977 kunlar

+1 04530 kunlar

3 022

Post ko'rishlar

~ 89224 soatlar

~ 1 13048 soatlar

5.69%

Muloqot nisbati

Ma'lumot yo'q

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😂😂

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Repost from Trump's Ear

#US #Trump 👂 More on Trump's Ear ⚠️

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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. → You'll learn how AI is used and how it's different from machine learning. 🔗 Course Link 2. Image Generation → Discover how to train and deploy a model to generate images. → After completing this course, you will be awarded a badge. 🔗 Course Link 3. Responsible AI → It explains what responsible AI is and why it's important. → Learn the 7 AI principles. 🔗 Course Link 4. Large Language Models → Explore what large language models (LLM) are. → How you can use prompting tuning to enhance LLM performance. 🔗 Course Link 5. Transformer and BERT Models → Two essential AI models. → How it is to build the BERT model. → Upon completion, you will be awarded a badge. 🔗 Course Link 6. Attention Mechanism → Introduce you to the attention mechanism. → Find out how it can be applied to enhance AI tasks' performance. 🔗 Course Link 7. Generative AI Studio → Integrate AI into your apps. → Find out about Generative AI Studio, what it can do, and it's features. 🔗 Course Link 8. Image recognition → Learn how to create an AI that understands images. → Practical learning so that you can create your own by the end of the course. 🔗 Course Link All the best 👍👍 #freecourses

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𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽𝘀 𝗧𝗼 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲😍 1️⃣ BCG Data Science & Analytics 2️⃣ TATA Data Visualization Internship 3️⃣ Accenture Data Analytics 4️⃣ PwC Power BI Internship 5️⃣ British Airways Data Science 6️⃣ Quantium Data Analytics 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4i9L0LA Enroll For FREE & Get Certified 🎓

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Data Scientist Roadmap 👆

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𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍 - SQL - Blockchain - HTML & CSS - Excel, and - Generative AI These free full courses will take you from beginner to expert! 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4gRuzlV Enroll For FREE & Get Certified 🎓

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Skills required to become an AI engineer

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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✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4k5x6vx No more excuses—just pure learning!✅️

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🔗 Master 8 Essential Machine Learning Algorithms

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🔗 Master 8 Essential Machine Learning Algorithms To truly master these foundational algorithms

It's crucial to dive deeper into their real-world applications and understand how AI is shaping the future.

That's where "The Most Effective Guide to Master AI" comes in! This comprehensive guide covers everything you need to know: - Real-world AI applications - Computer Vision - Generative Models - Essential AI tools

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Machine Learning Cheatsheet 💪

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𝗠𝗮𝘀𝘁𝗲𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻 – 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲!😍 Want to break into Machine Learning without spending a fortune?💡 This 100% FREE course is your ultimate guide to learning ML with Python from scratch!✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4k9xb1x 💻 Start Learning Now → Enroll Here✅️

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Generative AI Free Resources 👇👇 https://t.me/generativeai_gpt

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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 😍 1)Business Analysis – Foundation 2)Business Analysis Fundamentals 3)The Essentials of Business & Risk Analysis 4)Master Microsoft Power BI 𝗟𝗶𝗻𝗸 👇:- https://pdlink.in/4hHxBdW Enroll For FREE & Get Certified🎓

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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. 2. Work with Data Clean, preprocess & visualize datasets using Pandas, Seaborn, and Matplotlib for hands-on experience. 3. Master Machine Learning Understand supervised & unsupervised learning, regression, decision trees & implement models with Scikit-Learn. 4. Explore Deep Learning Learn neural networks, CNNs, RNNs, and Transformers using TensorFlow & PyTorch for AI applications. 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.