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SAMachine learning cheat sheet
#samaitechnologies #ai #machinelearning #cheatsheet #samaitech
@samai.tech
#Unsupervised Machine Learning
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CHMachine learning relies heavily on mathematical foundations.
#tech #ml #explore #fyp #ai
@chrisoh.zip
846
CODay 3 of our Machine Learning series 🚀
Today we broke down the three main types of Machine Learning:
Supervised, Unsupervised, and Reinforcement Learning.
Understanding these foundations makes everything ahead much easier.
From tomorrow, we start diving deep — beginning with Supervised Learning.
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#MachineLearning
#ArtificialIntelligence
#SupervisedLearning
#ReinforcementLearning
#CodeLoopa
@codeloopaa
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COA neural network visualizer that shows how an MLP learns step by step. Runs in the browser, trained with PyTorch, and works best on desktop.
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Source: 🎥 DFinsterwalder (X)
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#coding #programming #softwaredevelopment #computerscience #cse #software #ai #ml #machinelearning #computer #neuralnetwork #mlp #ai #machinelearning #deeplearning #visualization #threejs #pytorch #webapp #tech
@code_helping
571.2K
THNeural networks and machine learning.
@theartificialintelligence
941.0K
WOSteve brunton is sooo GOATEDDD !!!
#machinelearning #datascience #stem #artificialintelligence
@workiniterations
1.3M
SAI’ve been asked many times where to start learning ML, so after talking to so many experts in this field, this is a good place to start.
Comment down below “TRAIN” and I’ll send you a more in-depth checklist along with the best GitHub links to help you start learning each concept.
If you don’t receive the link you either need to follow first then comment, or your instagram is outdated. Either way, no worries. send me a dm and I’ll get it to you ASAP.
#cs #ai #dev #university #softwareengineer #viral #advice #machinelearning
@sambhav_athreya
10.7K
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
320.7K
COMachine Learning, explained by cats. #cat #code #ai #machinelearning #algorithm
@coding.kitty
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
1.1K
BKDay 3: Types of Machine Learning
#ai #ml #machinelearning #statistics
@bkhidake
454.9K
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
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Explore Unsupervised Machine Learning#machin#learning#learn#machine learning#machines#learnings#learned#unsupervised