Matrix in Machine Learning for Beginners - Search Videos

4 steps for machine learning beginners 😮‍💨

4 steps for machine learning beginners 😮‍💨

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AI • Machine Learning • Tech on Instagram: "Read our Weekly AI Newsletter—educational, easy to understand, mathematically explained, and completely free (link in bio 🔗). Backpropagation, a fundamental deep learning algorithm central to training neural networks, was popularized in the 1980s but has roots tracing back earlier. Paul Werbos is credited with formalizing backpropagation in his 1974 PhD thesis, providing a systematic way to compute gradients efficiently in multi-layer networks. Despit

AI • Machine Learning • Tech on Instagram: "Read our Weekly AI Newsletter—educational, easy to understand, mathematically explained, and completely free (link in bio 🔗). Backpropagation, a fundamental deep learning algorithm central to training neural networks, was popularized in the 1980s but has roots tracing back earlier. Paul Werbos is credited with formalizing backpropagation in his 1974 PhD thesis, providing a systematic way to compute gradients efficiently in multi-layer networks. Despit

155.4K views2 months ago

Instagramaibutsimple

Data Science | ML | AI Community 👩‍🏫 on Instagram: "📍Day 68: 9 machine learning algorithms every data scientist should know👇 1. Linear Regression: Used for predicting a continuous value. It’s simple yet effective for various problems. 2. Logistic Regression: Despite its name, it’s used for classification tasks, particularly binary classification. And I also use class probabilities (class proba), which is the probability of the class label. 3. Decision Trees: Used for both classification and

Data Science | ML | AI Community 👩‍🏫 on Instagram: "📍Day 68: 9 machine learning algorithms every data scientist should know👇 1. Linear Regression: Used for predicting a continuous value. It’s simple yet effective for various problems. 2. Logistic Regression: Despite its name, it’s used for classification tasks, particularly binary classification. And I also use class probabilities (class proba), which is the probability of the class label. 3. Decision Trees: Used for both classification and

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Instagramdatascienceschool

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