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#snsinstitutions #snsdesignthinkers #designthinking "Join the discussion on Linear Models, SVMs, and Perceptrons in deep learning! Understand how linear models form the foundation of AI, SVMs handle classification with hyperplanes, and perceptrons ignite the neural network revolution. Compare their strengths, limitations, and real-world applications. A must-watch for AI enthusiasts!"

#snsinstitutions #snsdesignthinkers #designthinking "Probability in deep learning measures uncertainty and guides predictions. It’s the foundation of models like neural networks, enabling tasks like classification and decision-making. From likelihood estimation to Bayesian inference, probabilities help optimize and generalize models. Dive into how AI leverages probabilities for smarter learning!"

#snsinstitutions #snsdesignthinkers #designthinking "Probability in deep learning measures uncertainty and guides predictions. It’s the foundation of models like neural networks, enabling tasks like classification and decision-making. From likelihood estimation to Bayesian inference, probabilities help optimize and generalize models. Dive into how AI leverages probabilities for smarter learning!"

#snsinstitutions #snsdesignthinkers #designthinking "Probability in deep learning measures uncertainty and guides predictions. It’s the foundation of models like neural networks, enabling tasks like classification and decision-making. From likelihood estimation to Bayesian inference, probabilities help optimize and generalize models. Dive into how AI leverages probabilities for smarter learning!"

#snsinstitutions #snsdesignthinkers #designthinking Norms in deep learning measure the size or magnitude of vectors and matrices, helping to quantify their properties. Common norms include the L1 norm (sum of absolute values) and the L2 norm (Euclidean distance), both used to regularize models and prevent overfitting. Norm-based regularization, like L2 regularization, adds a penalty to large we...

#snsinstitutions #snsdesignthinkers #designthinking Norms in deep learning measure the size or magnitude of vectors and matrices, helping to quantify their properties. Common norms include the L1 norm (sum of absolute values) and the L2 norm (Euclidean distance), both used to regularize models and prevent overfitting. Norm-based regularization, like L2 regularization, adds a penalty to large we...

#snsinstitutions #snsdesignthinkers #designthinking Norms in deep learning measure the size or magnitude of vectors and matrices, helping to quantify their properties. Common norms include the L1 norm (sum of absolute values) and the L2 norm (Euclidean distance), both used to regularize models and prevent overfitting. Norm-based regularization, like L2 regularization, adds a penalty to large we...

#snsinstitutions #snsdesignthinkers #designthinking Norms in deep learning measure the size or magnitude of vectors and matrices, helping to quantify their properties. Common norms include the L1 norm (sum of absolute values) and the L2 norm (Euclidean distance), both used to regularize models and prevent overfitting. Norm-based regularization, like L2 regularization, adds a penalty to large we...

#snsinstitutions #snsdesignthinkers #designthinking Norms in deep learning measure the size or magnitude of vectors and matrices, helping to quantify their properties. Common norms include the L1 norm (sum of absolute values) and the L2 norm (Euclidean distance), both used to regularize models and prevent overfitting. Norm-based regularization, like L2 regularization, adds a penalty to large we...

#snsinstitutions #snsdesignthinkers #designthinking Deep learning is a subset of machine learning that uses neural networks with multiple layers to process and analyze complex data. It excels in tasks like image recognition, natural language processing, and speech synthesis. Deep learning models are trained on large datasets and leverage high computational power to identify patterns and make pr...

#snsinstitutions #snsdesignthinkers #designthinking Deep learning is a subset of machine learning that uses neural networks with multiple layers to process and analyze complex data. It excels in tasks like image recognition, natural language processing, and speech synthesis. Deep learning models are trained on large datasets and leverage high computational power to identify patterns and make pr...

#snsinstitutions #snsdesignthinkers #designthinking Deep learning is a subset of machine learning that uses neural networks with multiple layers to process and analyze complex data. It excels in tasks like image recognition, natural language processing, and speech synthesis. Deep learning models are trained on large datasets and leverage high computational power to identify patterns and make pr...

#snsinstitutions #snsdesignthinkers #designthinking Deep learning is a subset of machine learning that uses neural networks with multiple layers to process and analyze complex data. It excels in tasks like image recognition, natural language processing, and speech synthesis. Deep learning models are trained on large datasets and leverage high computational power to identify patterns and make pr...

#snsinstitutions #snsdesignthinkers #designthinking Deep learning is a subset of machine learning that uses neural networks with multiple layers to process and analyze complex data. It excels in tasks like image recognition, natural language processing, and speech synthesis. Deep learning models are trained on large datasets and leverage high computational power to identify patterns and make pr...

LINEAR REGRESSION IN ML|N.PADMASHRI|SNS INSTITUTIONS

SEMINAR SUPERVISED LEARNING IN ML|N.PADMASHRI|SNS INSTITUTIONS

REINFORCEMENT LEARNING_1|N.PADMASHRI|SNS INSTITUTIONS

REINFORCEMENT LEARNING|N.PADMASHRI|SNS INSTITUTIONS

TESTING ML ALGORITHM|N.PADMASHRI|SNS INSTITUTIONS

TESTING ML ALGORITHM|N.PADMASHR||SNS INSTITUTIONS

LINEAR MODEL IN ML|N.PADMASHRI|SNS INSTITUTIONS

LINEAR MODEL IN ML|N.PADMASHRI|SNS INSTITUTIONS

GROUP DISCUSSION-SVM IN ML|N.PADMASHRI|SNS INSTITUTIONS

LECTURE SERIES-PCA IN ML|N.PADMASHRI|SNS INSTITUTIONS

CASE STUDY VIDEO IN ML| N.PADMASHRI|SNS INSTITUTIONS

LECTURE SERIES-DIMENSIONALITY REDUCTION IN ML|N.PADMASHRI|SNS INSTITUTIONS

LECTURE SERIES-CLUSTERING IN ML|N.PADMASHRI|SNS INSTITUTIONS

LECTURE SERIES-PCA IN ML|N.PADMASHRI|SNS INSTITUTIONS

LECTURE SERIES-LVM IN ML|N.PADMASHRI|SNS INSTITUTIONS