Artificial Intelligence
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🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data
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Red:📈 Análisis del canal de Telegram Artificial Intelligence
El canal Artificial Intelligence (@machinelearning_deeplearning) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 55 377 suscriptores, ocupando la posición 3 050 en la categoría Educación y el puesto 6 211 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 55 377 suscriptores.
Según los últimos datos del 30 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 683, y en las últimas 24 horas de 41, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.87%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.33% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 3 250 visualizaciones. En el primer día suele acumular 736 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 25.
- Intereses temáticos: El contenido se centra en temas clave como learning, classification, layer, pattern, chatbot.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“🔰 Machine Learning & Artificial Intelligence Free Resources
🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more
For Promotions: @love_data”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 31 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.
55 377
Suscriptores
+4124 horas
+1517 días
+68330 días
Archivo de publicaciones
55 387
Russia is currently hosting the AI Journey international conference, during which the second season of the AI4PLANET scientific and educational video podcast was released.
The main topic of this season was the role of AI in the emergence of new professions and transformation of existing ones. The speakers of the podcast discussed in 10 episodes how AI is already helping experts and what are the prospects of using AI in the work of ecologists, climatologists, doctors, teachers, HR-specialists and security officers.
The experts sought answers to the burning questions:
▫️ How will AI strengthen the skills of the in-demand specialist of the future?
▫️ Do scientists and researchers already need to master Data Science skills now?
▫️ AI-developer for sustainable development - a new profession or a collective image of coordinated interdisciplinary work of a large team?
AI4PLANET is a technological “journey” through professions from different fields of sustainable development: from climate and ecology to psychology and professions of the future.
We invite you to visit the AI Journey international conference page and listen to the AI4PLANET video podcast.
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ARTIFICIAL INTELLIGENCE 🤖
🎥 Siraj Raval - YouTube channel with tutorials about AI.
🎥 Sentdex - YouTube channel with programming tutorials.
⏱ Two Minute Papers - Learn AI with 5-min videos.
✍️ Data Analytics - blog on Medium.
🎓 Google Machine Learning Course - A crash course on machine learning taught by Google engineers.
🌐 Google AI - Learn from ML experts at Google.
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AI/ML Roadmap👨🏻💻👾🤖 -
==== Step 1: Basics ====
📊 Learn Math (Linear Algebra, Probability).
🤔 Understand AI/ML Fundamentals (Supervised vs Unsupervised).
==== Step 2: Machine Learning ====
🔢 Clean & Visualize Data (Pandas, Matplotlib).
🏋️♂️ Learn Core Algorithms (Linear Regression, Decision Trees).
📦 Use scikit-learn to implement models.
==== Step 3: Deep Learning ====
💡 Understand Neural Networks.
🖼️ Learn TensorFlow or PyTorch.
🤖 Build small projects (Image Classifier, Chatbot).
==== Step 4: Advanced Topics ====
🌳 Study Advanced Algorithms (Random Forest, XGBoost).
🗣️ Dive into NLP or Computer Vision.
🕹️ Explore Reinforcement Learning.
==== Step 5: Build & Share ====
🎨 Create real-world projects.
🌍 Deploy with Flask, FastAPI, or Cloud Platforms.
#ai #ml
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💻Free chat gpt alternative
Link 🔗
https://gpt4o.so/app
Without any login Infact you can upload your pdf documents to ask answer best site for students who were looking for chat gpt 4 now enjoy it
⚡️Give Reactions 🙌
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💸 SECOND AND LAST TRADING SESSION: THE RESULTS SPEAK FOR THEMSELVES! 💸
Here is the end of the second trading session, and as always, I am thrilled with the results! 💥📈
It wasn't just a trading session - it was a WIN! Each of you can repeat these results just by following the signals and not being afraid to act! 🚀
We were able to earn $5,900 starting from $200! Anyone could do it.
From tomorrow we start a new marathon :
⚡️Start : 400$
🤑Goal : $12,000
⌛Deadline : 10 days!
Everyone can participate absolutely free of charge! Go to the channel and start trading. Write in private messages to Lisa : “TRADING”. At the link below
t.me/traderlisa
t.me/traderlisa
t.me/traderlisa
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10 Things you need to become an AI/ML engineer:
1. Framing machine learning problems
2. Weak supervision and active learning
3. Processing, training, deploying, inference pipelines
4. Offline evaluation and testing in production
5. Performing error analysis. Where to work next
6. Distributed training. Data and model parallelism
7. Pruning, quantization, and knowledge distillation
8. Serving predictions. Online and batch inference
9. Monitoring models and data distribution shifts
10. Automatic retraining and evaluation of models
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🎓 Land your Dream Data Science and AI Job
🌟 2000+ Students Placed
💰 7.2 LPA Average Package
🚀 41 LPA Highest Package
🤝 450+ Hiring Partners
Register for FREE Now: https://tracking.acciojob.com/g/PUfdDxgHR
ENJOY LEARNING 👍👍
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Hard Pill To Swallow: 💊
Robots aren’t stealing your future - they’re taking the boring jobs.
Meanwhile:
- Some YouTuber made six figures sharing what she loves.
- A teen's random app idea just got funded.
- My friend quit banking to teach coding - he's killing it.
Here’s the thing:
Hard work still matters. But the rules of the game have changed.
The real money is in solving problems, spreading ideas, and building cool stuff.
Call it evolution. Call it disruption. Whatever.
Crying about the old world won't help you thrive in the new one.
Create something.✨
#ai
55 387
AI Engineer
Deep Learning: Neural networks, CNNs, RNNs, transformers.
Programming: Python, TensorFlow, PyTorch, Keras.
NLP: NLTK, SpaCy, Hugging Face.
Computer Vision: OpenCV techniques.
Reinforcement Learning: RL algorithms and applications.
LLMs and Transformers: Advanced language models.
LangChain and RAG: Retrieval-augmented generation techniques.
Vector Databases: Managing embeddings and vectors.
AI Ethics: Ethical considerations and bias in AI.
R&D: Implementing AI research papers.
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What kind of problems neural nets can solve?
Neural nets are good at solving non-linear problems. Some good examples are problems that are relatively easy for humans (because of experience, intuition, understanding, etc), but difficult for traditional regression models: speech recognition, handwriting recognition, image identification, etc.
55 387
FREE Stock Marketing Resources
👇👇
https://chat.whatsapp.com/GNcP0K58yTsAJ72CxSEUtj
(Only for Indian Users)
55 387
Free Stock Marketing & Finance Resources 👇👇
https://chat.whatsapp.com/F4q9qpeJSmu7XD8ctqnIhr
(Only for Indian Users)
