316.4K
COMachine Learning, explained by cats. #cat #code #ai #machinelearning #algorithm
@coding.kitty
#Machine Learning Algorithm
世界中の人々によるMachine Learning Algorithmに関する15K件のリール動画を視聴。
ログインせずに匿名で視聴。
15K posts
NewTrendingViral
関連検索
30machine learning algorithm typesalgorithmemachine learning algorithm examplesmachine learning algorithm visualizationsvm vs other machine learning algorithmsdifference between algorithm and machine learningalgorithms vs machine learningalgorithmalgorithms in machine learningmachine learning algorithms explained
トレンドリール
(12)
1.2M
CHMachine learning relies heavily on mathematical foundations.
#tech #ml #explore #fyp #ai
@chrisoh.zip
54.9K
AILogistic regression is an algorithm and statistical method used in machine learning for binary classification tasks, where the goal is to predict one of two possible outcomes (for example, yes or no).
Logistic regression outputs probabilities that a certain event will occur, using the logistic function to transform the linear output of a model into a probability value from 0 to 1. It’s used mainly for cases where the variable is categorical.
The model learns from the data by finding the best set of weights (also the coefficients of the curve) that minimize the error between the model’s predicted and actual values.
Logistic regression is useful since it’s simple, easy to interpret, and effective for simple classification problems and serves as a good introduction to machine learning.
C: 3 minute data science
Join our AI community for more posts like this @aibutsimple 🤖
#datascientist #computerengineering #deeplearning #computerscience #math #mathematics #ml #logisticregression #machinelearning #datascience #education #coding #programming #learning #courses #bootcamp #course
@aibutsimple
570.6K
THNeural networks and machine learning.
@theartificialintelligence
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If you don’t receive the link you either need to follow first then comment, or your instagram is outdated.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
3.0M
ITcomment ‘AI’ and I’ll send you the link in your DMs
this is such a great resource to guide you on your AI/ML journey!
#techcareer #ai #machinelearning #careergrowthtips #datascience #coding
@itsallykrinsky
132.4K
KRVisualizing the architecture of intelligence. 🕸️✨
Every neural network is built on the same fundamental concept: Layers.
🟡 Input Layer: Receives the raw data (pixels, text, numbers).
🟢 Hidden Layers: Where the magic happens—processing features and finding patterns.
🟠 Output Layer: Delivers the final prediction or decision.
From the simple Perceptron to the complex loops of an RNN, these structures are the blueprints for how machines learn. 📐
#NeuralNetworks #MachineLearning #DeepLearning #DataScience #AI #Education #Visualized
@kreggscode
158.2K
EQThe Secret Behind Machine Learning Predictions! Ever wondered how machines make binary decisions? This video breaks down Logistic Regression using the Sigmoid Function. We visualize how the weight (w) controls the steepness of the curve and how the bias (b) shifts it along the x-axis. See how Cross-Entropy (CE) Loss is minimized to find the optimal fit for your data points. Finally, we explore the decision boundary at P=0.5, which separates predictions into Class 0 and Class 1. Perfect for data science students and machine learning enthusiasts looking for a quick, intuitive visualization of classification algorithms and mathematical optimization. #LogisticRegression #MachineLearning #SigmoidFunction #Math #Manim
@equationsinmotion
58.6K
EMThese are some of the best beginner-friendly resources I’ve found to actually understand machine learning.
Nothing overly complicated, just what you need to get the concepts and start building.
Comment ML and I’ll send you all the resources.
@emrcodes
12.0K
KAWhat is xgboost in machine learning and why it beats random forest #ml #datascientist
@karinadatascientist
1.4M
INGraham scan algorithm animated!
Full video in the YouTube channel
#algorithms #computerscience #programming
@inside.code
706.2K
AILarge Language Models (LLMs) such as ChatGPT are based on neural networks called transformers, an architecture built using multiple attention mechanisms and multilayer perceptrons (MLPs).
These models process input text by learning context through self-attention mechanisms, which weighs the importance of each pair of words. This way, long sequences are no longer an issue.
This contextual understanding is passed through MLPs, which learn the representations and patterns of the sequence.
To generate text, the model generates a probability distribution of the next word; we choose the highest-probability word and keep predicting the next word, iterating to create a sentence or paragraph.
C: 3blue1brown
Join our AI community for more posts like this @aibutsimple 🤖
#neuralnetwork #llm #gpt #artificialintelligence #machinelearning #3blue1brown #deeplearning #neuralnetworks #datascience #python #ml #pythonprogramming #datascientist
@aibutsimple
✨ #Machine Learning Algorithm発見ガイド
Instagramには#Machine Learning Algorithmの下に15K件の投稿があり、プラットフォームで最も活気のあるビジュアルエコシステムの1つを作り出しています。
#Machine Learning Algorithmは現在、Instagram で最も注目を集めているトレンドの1つです。このカテゴリーには15K以上の投稿があり、@itsallykrinsky, @inside.code and @sambhav_athreyaのようなクリエイターがバイラルコンテンツでリードしています。Pictameでこれらの人気動画を匿名で閲覧できます。
#Machine Learning Algorithmで何がトレンドですか？最も視聴されたReels動画とバイラルコンテンツが上部に掲載されています。
人気カテゴリー
📹 ビデオトレンド: 最新のReelsとバイラル動画を発見
📈 ハッシュタグ戦略: コンテンツのトレンドハッシュタグオプションを探索
🌟 注目のクリエイター: @itsallykrinsky, @inside.code, @sambhav_athreyaなどがコミュニティをリード
#Machine Learning Algorithmについてのよくある質問
Pictameを使用すれば、Instagramにログインせずに#Machine Learning Algorithmのすべてのリールと動画を閲覧できます。あなたの視聴活動は完全にプライベートです。ハッシュタグを検索して、トレンドコンテンツをすぐに探索開始できます。
パフォーマンス分析
12リールの分析
💡 トップ投稿は平均1.7M回の再生（平均の2.3倍）
週3-5回、活動時間に定期的に投稿
コンテンツ作成のヒントと戦略
💡 トップコンテンツは10K以上再生回数を獲得 - 最初の3秒に集中
📹 #Machine Learning Algorithmには高品質な縦型動画（9:16）が最適 - 良い照明とクリアな音声を使用
✍️ ストーリー性のある詳細なキャプションが効果的 - 平均長390文字
✨ 多くの認証済みクリエイターが活動中（33%） - コンテンツスタイルを研究
#Machine Learning Algorithm に関連する人気検索
🎬動画愛好家向け
Machine Learning Algorithm ReelsMachine Learning Algorithm動画を見る
📈戦略探求者向け
Machine Learning Algorithmトレンドハッシュタグ最高のMachine Learning Algorithmハッシュタグ
🌟もっと探索
Machine Learning Algorithmを探索#machine learning algorithm types#algorithme#machine learning algorithm examples#machine learning algorithm visualization#svm vs other machine learning algorithms#difference between algorithm and machine learning#algorithms vs machine learning#algorithm