Machine Learning – Telegram
Machine Learning
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Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.

Admin: @HusseinSheikho || @Hussein_Sheikho
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🤖🧠 Granite-Speech-3.3-8B: IBM’s Next-Gen Speech-Language Model for Enterprise AI

🗓️ 14 Oct 2025
📚 AI News & Trends

In the fast-growing field of speech and language AI, IBM continues to make strides with its Granite model family , a suite of open enterprise-grade AI models that combine accuracy, safety and efficiency. The latest addition to this ecosystem, Granite-Speech-3.3-8B marks a significant milestone in automatic speech recognition (ASR) and speech translation (AST) technology. Released ...

#SpeechAI #LanguageModel #EnterpriseAI #ASR #SpeechTranslation #GraniteModel
🤖🧠 LLaMAX2 by Nanjing University, HKU, CMU & Shanghai AI Lab: A Breakthrough in Translation-Enhanced Reasoning Models

🗓️ 14 Oct 2025
📚 AI News & Trends

The world of large language models (LLMs) has evolved rapidly, producing advanced systems capable of reasoning, problem-solving, and creative text generation. However, a persistent challenge has been balancing translation quality with reasoning ability. Most translation-enhanced models excel in linguistic diversity but falter in logical reasoning or coding tasks. Addressing this crucial gap, the research paper ...

#LLaMAX2 #TranslationEnhanced #ReasoningModels #LargeLanguageModels #NanjingUniversity #HKU
🤖🧠 Diffusion Transformers with Representation Autoencoders (RAE): The Next Leap in Generative AI

🗓️ 14 Oct 2025
📚 AI News & Trends

Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ...

#DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace
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📌 Using Decision Trees for Exploratory Data Analysis

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-20 | ⏱️ Read time: 7 min read

Add decision trees to your EDA and get great insights from the start
📌 Optimizing Sigma Rules in Spark with the Aho-Corasick Algorithm

🗂 Category: CYBERSECURITY

🕒 Date: 2024-06-20 | ⏱️ Read time: 9 min read

Extending Spark for improved performance in handling multiple search terms
📌 Exploratory Data Analysis in 11 Steps

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-19 | ⏱️ Read time: 6 min read

Starting an exploratory data analysis can be daunting. How do you know what to look…
🔗 Keras vs. TensorFlow vs. PyTorch: The ultimate showdown for deep learning supremacy! 🚀

🤔 Keras: The user-friendly champion! Perfect for beginners and rapid prototyping.

⚡️ TensorFlow: The powerhouse! Great for complex projects with extensive capabilities.

🔥 PyTorch: The flexible innovator! With its dynamic computation graph, it’s a favorite among researchers.

👉 @codeprogrammer
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📌 How I Dockerized Apache Flink, Kafka, and PostgreSQL for Real-Time Data Streaming

🗂 Category: DATA ENGINEERING

🕒 Date: 2024-06-19 | ⏱️ Read time: 12 min read

Integrating pyFlink, Kafka, and PostgreSQL using Docker
📌 A Step-By-Step Guide to Building a Programming Language

🗂 Category: PROGRAMMING

🕒 Date: 2024-06-19 | ⏱️ Read time: 20 min read

Building a programming language from scratch in a few hours
📌 Counts Outlier Detector: Interpretable Outlier Detection

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-19 | ⏱️ Read time: 22 min read

An interpretable outlier detector based on multi-dimensional histograms.
📌 CLIP, LLaVA, and the Brain

🗂 Category: DEEP LEARNING

🕒 Date: 2024-06-19 | ⏱️ Read time: 10 min read

What neuroscience can teach us about the limitations of modern multimodal transformers
📌 3 Simple Statistical Methods for Outlier Detection

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-18 | ⏱️ Read time: 6 min read

If it works, keep it simple
📌 Creating an Assistant with OpenAI Assistant API and Streamlit

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-06-18 | ⏱️ Read time: 7 min read

A step-by-step guide
📌 Let’s Revisit Case-When in Different Libraries Including the New Player: Pandas

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-18 | ⏱️ Read time: 6 min read

How to create conditional columns with different tools.
📌 AI Agent Capabilities Engineering

🗂 Category: CHATGPT

🕒 Date: 2024-06-18 | ⏱️ Read time: 13 min read

Introducing a high-level capabilities engineering framework for AI Agents
📌 Managing Pivot Table and Excel Charts with VBA

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-18 | ⏱️ Read time: 10 min read

Save precious hours by automating working with pivot tables and charts using VBA
📌 Foundation Models in Graph & Geometric Deep Learning

🗂 Category:

🕒 Date: 2024-06-18 | ⏱️ Read time: 28 min read

In this post, we argue that the era of Graph FMs has already begun and…
📌 Learning Triton One Kernel at a Time: Matrix Multiplication

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-10-14 | ⏱️ Read time: 14 min read

Tiled GEMM, GPU memory, coalescing, and much more!
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📌 Building A Successful Relationship With Stakeholders

🗂 Category: DATA SCIENCE

🕒 Date: 2025-10-14 | ⏱️ Read time: 12 min read

Show your value by moving beyond the technical
📌 Why AI Still Can’t Replace Analysts: A Predictive Maintenance Example

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-10-14 | ⏱️ Read time: 7 min read

Learn about the limitations of AI in analytics through the example of bearing vibration data…
📌 Human Won’t Replace Python

🗂 Category: PROGRAMMING

🕒 Date: 2025-10-14 | ⏱️ Read time: 23 min read

Why vibe-coding is not a step up from “classic” coding — and why it matters