1.2M
CHMachine learning relies heavily on mathematical foundations.
#tech #ml #explore #fyp #ai
@chrisoh.zip
#Arima Vs Machine Learning
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CODay 1 of our Machine Learning series 🚀
We started with the basics — what machine learning really is and how it works.
This series is for anyone who wants to understand ML without confusion.
Next up: AI vs Machine Learning.
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#MachineLearning
#ArtificialIntelligence
#CodeLoopa
#LearnAI
#TechExplained
@codeloopaa
456.7K
CHHere’s your full roadmap on how to get into machine learning. Comment “Roadmap” to get the pdf.
Save and follow for more.
#ai #machinelearning #coding #programming #cs
@chrispathway
14.0K
ZAMachine Learning 🤍
@zararzln
125.4K
SAAI vs Machine Learning VS Deep Learning BREAKDOWN 😤 #ai #ml #tech #fyp
@sajjaad.khader
336.2K
PI2025 machine learning roadmap - it’s time to start prepping for AI’s takeover 💡🤖 resources mentioned:
VIDEO:
Full Applied AI Lectures by Cassie Kozyrkov
Neural Networks: Zero to Hero by Andrej Karpathy
Machine Learning Specialization by Andrew Ng
BOOKS:
An Introduction to Statistical Learning
Mathematics for Machine Learninf
Artificial Intelligence: A Modern Approach
FOR PRACTICE:
Machine Learning with PyTorch and Scikit-Learn
AIML.com
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#machinelearning #ai #resources #tech #programming #womenintech #coder #programacao #latinasintech #swe
@pikacodes
236.1K
CATension mat lena ye next year syllabus mein ayega.
#machinelearning #computerscience #researchpaper #Transformers #artificialintelligence
@cactuss.ai
23.0K
LEThe first real step isn't just looking at charts,it’s mastering Machine Learning from the ground up. If you want to move past the basics and learn the foundations from an expert with 5 years of industry experience, this is for you.
Learn from A to Z. No fluff. Just engineering.
#DataScience #MachineLearning #AIEngineer #PythonCoding #TechCareer #LearnSmartX #100DaysOfCode
@learnsmartx
1.7K
PYDe intuición a pronóstico: qué es ARIMA, estacionariedad, diferenciación, elegir p y q (ACF/PACF) y checklist de validación. #DataScience #SeriesDeTiempo #ARIMA #MachineLearning #Python #Estadistica #Forecasting #Analytics #IA
@pypromx
10.8K
PEPutting machine learning mathematics prerequisites into context, to better appreciate their significance.
Resources used:
- Deisenroth at al, Mathematics for Machine Learning, 2020
- Goodfellow et al, Deep Learning, 2016
- MathAcademy
@petal.byte
14.5K
SUComment “ML” for more resources if you want to learn more about machine learning and AI…
YouTube Channel Names:
Tech with Tim,IBM Technologies, Andrew Ng(Lex Friedman Podcast)
#coding #computerscience #machinelearning #ai
@sujar.tech
69.0K
AIIf you want to learn AI in 2026, here's where to start:
First, build a strong foundation in machine learning before moving into deep learning.
Begin with supervised methods like linear and logistic regression to understand optimization and decision boundaries, then explore KNN, Naive Bayes, decision trees, random forests, gradient boosting, and SVMs to see different modeling assumptions and performance trade-offs.
Next, study unsupervised techniques such as k-means and hierarchical clustering, Gaussian mixture models, and dimensionality reduction methods like PCA, t-SNE, and UMAP to learn how structure can be discovered without labels.
With this in mind, transition to deep learning by learning neural networks and autoencoders, then more specialized architectures like CNNs for vision, RNNs for sequences, transformers and LLMs for language, and diffusion models for generative tasks.
This progression builds intuition step by step, from classical algorithms to modern AI systems.
If you want to commit to learning AI, Join 7000+ Others in our Visually Explained AI Newsletter. It's easy to understand, with math included—it's also completely free. The link is in our bio 🔗.
Join our AI community for more posts like this @aibutsimple 🤖
#machinelearning #deeplearning #statistics #computerscience #coding #mathematics #math #physics #science #education
@aibutsimple
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