AI and Machine Learning

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Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses

India3 020 Education1 561...

📈 Analytical overview of Telegram channel AI and Machine Learning

Channel AI and Machine Learning (@machine_learning_courses) in the English language segment is an active participant. Currently, the community unites 94 048 subscribers, ranking 1 561 in the Education category and 3 020 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 94 048 subscribers.

According to the latest data from 24 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 986 over the last 30 days and by 67 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 6.50%. Within the first 24 hours after publication, content typically collects 1.56% reactions from the total number of subscribers.
Post reach: On average, each post receives 6 109 views. Within the first day, a publication typically gains 1 470 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
Thematic interests: Content is focused on key topics such as learning, llm, linkedin, linux, udemy.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses”

Thanks to the high frequency of updates (latest data received on 25 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.

94 048

Subscribers

+6724 hours

+1517 days

+98630 days

6 109

Post views

~ 1 47024 hours

~ 1 84148 hours

6.50%

Engagement rate

~ 1

Posts per day

Ads index

beta

Posts Archive

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🔗 Roadmap to master Machine Learning

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🔗 Roadmap to master Machine Learning

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🔗 The Only roadmap you need to become an ML Engineer 🥳 Phase 1: Foundations (1-2 Months) 🔹 Math & Stats Basics – Linear Algebra, Probability, Statistics 🔹 Python Programming – NumPy, Pandas, Matplotlib, Scikit-Learn 🔹 Data Handling – Cleaning, Feature Engineering, Exploratory Data Analysis Phase 2: Core Machine Learning (2-3 Months) 🔹 Supervised & Unsupervised Learning – Regression, Classification, Clustering 🔹 Model Evaluation – Cross-validation, Metrics (Accuracy, Precision, Recall, AUC-ROC) 🔹 Hyperparameter Tuning – Grid Search, Random Search, Bayesian Optimization 🔹 Basic ML Projects – Predict house prices, customer segmentation Phase 3: Deep Learning & Advanced ML (2-3 Months) 🔹 Neural Networks – TensorFlow & PyTorch Basics 🔹 CNNs & Image Processing – Object Detection, Image Classification 🔹 NLP & Transformers – Sentiment Analysis, BERT, LLMs (GPT, Gemini) 🔹 Reinforcement Learning Basics – Q-learning, Policy Gradient Phase 4: ML System Design & MLOps (2-3 Months) 🔹 ML in Production – Model Deployment (Flask, FastAPI, Docker) 🔹 MLOps – CI/CD, Model Monitoring, Model Versioning (MLflow, Kubeflow) 🔹 Cloud & Big Data – AWS/GCP/Azure, Spark, Kafka 🔹 End-to-End ML Projects – Fraud detection, Recommendation systems Phase 5: Specialization & Job Readiness (Ongoing) 🔹 Specialize – Computer Vision, NLP, Generative AI, Edge AI 🔹 Interview Prep – Leetcode for ML, System Design, ML Case Studies 🔹 Portfolio Building – GitHub, Kaggle Competitions, Writing Blogs 🔹 Networking – Contribute to open-source, Attend ML meetups, LinkedIn presence The data field is vast, offering endless opportunities so start preparing now.

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🚀 Whisper AI is Now on Telegram! Turn any audio, video, or YouTube content into accurate transcripts, concise summaries, and smart task executions — all powered by GPT-4o and Claude Sonnet! • Download videos directly by link • Supports 120+ languages • 99% transcription accuracy • Processes up to 6+ hours of audio seamlessly The entire process — from downloading a video by link to generating summaries and tasks — is handled automatically. 👉 Try it now

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🔅 08 - FineTuning LLMs

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🔅 07 - LLM Context Window

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🔅 06 - LLM Parameters

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🔅 05 - Inside an LLM Under the Hood

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🔅 04 - How LLMs generate text

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🔅 03 - Who invented LLMs

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🔅 02 - Ingredients of an LLM

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🔅 01 - Introduction to LLMs

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LLMs Intuition 01 - Introduction to LLMs 02 - Ingredients of an LLM 03 - Who invented LLMs 04 - How LLMs generate text 05 - Inside an LLM Under the Hood 06 - LLM Parameters 07 - LLM Context Window 08 - FineTuning LLMs

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📦 Exercise Files