Coding_knowledge
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💡 Your Coding Journey Starts Here! Get free courses, coding resources, internships, job updates & much more. Stay ahead in tech with us! ❤️🚀 Join our WhatsApp group👇 https://whatsapp.com/channel/0029Vaa7CVhCRs1rxJzy1n3D
Mostrar más📈 Análisis del canal de Telegram Coding_knowledge
El canal Coding_knowledge (@coding_knwledge01) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 79 500 suscriptores, ocupando la posición 1 554 en la categoría Tecnologías y Aplicaciones y el puesto 3 813 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 79 500 suscriptores.
Según los últimos datos del 29 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -930, y en las últimas 24 horas de -14, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 8.66%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.65% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 6 886 visualizaciones. En el primer día suele acumular 2 106 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 15.
- Intereses temáticos: El contenido se centra en temas clave como q&a, goody, api, stack, analyst.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“💡 Your Coding Journey Starts Here!
Get free courses, coding resources, internships, job updates & much more.
Stay ahead in tech with us! ❤️🚀
Join our WhatsApp group👇
https://whatsapp.com/channel/0029Vaa7CVhCRs1rxJzy1n3D”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 30 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 Tecnologías y Aplicaciones.
79 500
Suscriptores
-1424 horas
-1667 días
-93030 días
Archivo de publicaciones
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✅ Artificial Intelligence (AI) Acronyms You Must Know 🤖🧠
AI → Artificial Intelligence
AGI → Artificial General Intelligence
ASI → Artificial Superintelligence
ML → Machine Learning
DL → Deep Learning
RL → Reinforcement Learning
NLP → Natural Language Processing
CV → Computer Vision
ASR → Automatic Speech Recognition
TTS → Text To Speech
LLM → Large Language Model
VLM → Vision Language Model
MoE → Mixture of Experts
ANN → Artificial Neural Network
DNN → Deep Neural Network
CNN → Convolutional Neural Network
RNN → Recurrent Neural Network
GAN → Generative Adversarial Network
VAE → Variational Autoencoder
GNN → Graph Neural Network
RAG → Retrieval Augmented Generation
LoRA → Low Rank Adaptation
PEFT → Parameter Efficient Fine Tuning
RLHF → Reinforcement Learning with Human Feedback
API → Application Programming Interface
SDK → Software Development Kit
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⚠️ AI Mistakes Developers Make
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❌ Shipping untested AI code
❌ Ignoring edge cases
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#techinfo
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IIT Roorkee has launched its Python certification course, in which Python will be taught from basic to advanced level by IIT professors. If you want to study from IIT professors, book your test now. 👇
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Hey folks,
IIT Roorkee has launched its AI and Data Science certification course. You can get access by passing a ₹99 test, and the course will be taught live by IIT professors. So if you can pass the test and want to learn live from IIT professors, book the test using the link given below. The test will be held on 8th February.
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These are all new openings for freshers , find the relevant opening according to your degree and apply
Keep Following @Coding_knowledge for more such amazing updates!!
React ❤️ For More
79 487
✅ Complete Roadmap to Master Artificial Intelligence in 3 Months
Month 1: Foundations
- Week 1: AI basics
- What artificial intelligence is
- AI vs machine learning vs deep learning
- Real business use cases
Outcome: You know where AI fits in real products.
- Week 2: Math and logic essentials
- Linear algebra basics, vectors, matrices
- Probability and statistics basics
- Cost functions and optimization idea
Outcome: You understand how models learn.
- Week 3: Python for AI
- Python syntax for analysis
- NumPy arrays and operations
- Pandas for data handling
Outcome: You work with data confidently.
- Week 4: Data preparation
- Data cleaning and preprocessing
- Handling missing values and outliers
- Feature selection basics
Outcome: Your data is model ready.
Month 2: Machine Learning Core
- Week 5: Supervised learning
- Linear and logistic regression
- Decision trees and random forest
- Model evaluation, accuracy, precision, recall
Outcome: You build prediction models.
- Week 6: Unsupervised learning
- K-means clustering
- Hierarchical clustering
- PCA with real examples
Outcome: You find patterns in data.
- Week 7: Model improvement
- Overfitting and underfitting
- Cross validation
- Hyperparameter tuning
Outcome: Your models perform better.
- Week 8: Intro to deep learning
- Neural network basics
- Activation functions
- Backpropagation concept
Outcome: You understand how deep models work.
Month 3: Applied AI and Job Prep
- Week 9: Deep learning tools
- TensorFlow or PyTorch basics
- Build a simple neural network
- Train and test models
Outcome: You build neural models.
- Week 10: Real world AI project
- Choose use case, spam detection or sales prediction
- Data prep, model training, evaluation
- Simple deployment demo
Outcome: One strong AI project.
- Week 11: Interview preparation
- Machine learning theory questions
- Model selection questions
- Project explanation flow
Outcome: You answer with clarity.
- Week 12: Resume and practice
- AI focused resume
- GitHub with notebooks and projects
- Daily problem solving
Outcome: You are AI job ready.
Practice platforms: Kaggle, Google Colab, Scikit-learn docs
Double Tap ♥️ For Detailed Explanation of Each Topic
