#mlminiseries 검색 결과

Mini Series #MLMiniSeries #RNN A Recurrent Neural Network (RNN) is a type of neural network that processes sequences of inputs and produces sequences of outputs. It is commonly used in natural language processing, image recognition, and time series analysis.

#MLminiSeries #CNN: A Convolutional Neural Network is a type of deep learning AI used for image recognition & classification tasks. It takes an input image, passes it through multiple convolution layers, and produces an output of class probabilities. #AI #DeepLearning

#MLminiSeries #ActivationFunctions An activation function is a non-linear transformation that is applied to the input of a node in a neural network to determine the output of the node. It is a mathematical function used to determine the output of a neural network.

#MLminiSeries #Backpropagation Backpropagation is an algorithm used to calculate the error contribution of each neuron after a batch of data. It is used in supervised learning to update the weights and biases of the neural network.

#MLminiSeries #FeedforwardNN A feedforward neural network is a type of artificial neural network in which information flows only in one direction, from input to output, without forming a cycle. It is a basic type of artificial neural network.

#MLminiSeries #Stacking is an ensemble machine learning technique where multiple models are trained and combined to create a stronger model with improved accuracy. It is used to improve the performance of a single model.

#MLminiSeries #Boosting is a machine learning technique used to improve the accuracy of a model by combining the predictions of multiple weak learners. It works by sequentially adding models to the ensemble, each of which corrects the errors of its predecessors.

#MLMiniSeries #Bagging: Bagging is an ensemble machine learning technique used to improve the accuracy of predictions by combining the results from multiple models. It works by training each model using a different random subset of the data.

#MLminiSeries #EnsembleLearning Ensemble Learning is a technique that combines multiple machine learning models to improve the predictive accuracy of complex tasks. It is used to reduce variance, bias, and improve the accuracy of a model.

#MLMiniSeries #HyperparameterTuning Hyperparameter Tuning is the process of finding the best values for a model's hyperparameters to optimize its performance. It is used to optimize the performance of models and algorithms by tuning their parameters to the optimal values.

#MLminiSeries #CrossValidation Cross-Validation is a technique used in Machine Learning to evaluate models by partitioning the data into subsets. It helps to assess how the model will generalize to an independent dataset.

#MLMiniSeries #ConfusionMatrix A confusion matrix is a table that is used to evaluate the performance of a classification model. It is a table of the predicted classes against the actual classes. It helps to identify the types of errors made by a classifier.

#MLminiSeries #F1Score F1 Score is a metric used to measure the accuracy of a model. It is the harmonic mean of precision and recall, which takes both false positives and false negatives into account.

#MLminiSeries #Recall: The ability of a model to correctly identify all relevant instances of a class. It is the ability of a classifier to identify all relevant instances from a dataset. #ML #AI

#MLminiSeries #Precision: Precision is the fraction of relevant instances among the retrieved instances. It measures the relevancy of the results. It is the ratio of true positives to the sum of true positives and false positives.

#MLminiSeries #EvalMetrics Evaluation Metrics are used to measure the performance of a Machine Learning model. They help to compare different models and select the best one.

#MLminiSeries #Eclat: Eclat is an algorithm used for frequent itemset mining and association rule learning over transactional databases. It is an improved version of Apriori algorithm and is used to find frequent itemsets in a dataset.

#MLminiSeries #Apriori: Apriori is an algorithm used in market-basket analysis to identify associations between items in large datasets. It is used to uncover relationships between items in large datasets such as transactions, sales, and customer preferences.

#MLminiSeries #AssociationRules: Association Rule Learning is a type of Machine Learning algorithm used to identify relationships between variables in large datasets. It is used to discover interesting patterns in data such as frequent item sets & strong rules.

mini series #MLminiSeries #tSNE t-SNE is a nonlinear dimensionality reduction technique used to visualize high-dimensional datasets. It creates a map of the data, preserving the relative distances between points so that similar data points are grouped together.

#MLMiniSeries, for bite-sized AI and ML topics! 🚀✨ Discover mini nuggets of information, perfect for quick reference, understanding key terms, and mastering theory basics. Use #MLminiSeries to see all the tweets 📚🔍#AI #MachineLearning #DataScience