3/11/2024 0 Comments Convert jpg to csv keras exampleSpark Basics – Spark installation guide, Spark configuration, Memory management, Executor memory vs. coarse-grained update, Spark Hadoop YARN, HDFS Revision, and YARN Revision, The overview of Spark and how it is better than Hadoop, Deploying Spark without Hadoop, Spark history server and Cloudera distribution Introduction to Spark – Introduction to Spark, Spark overcomes the drawbacks of working on MapReduce, Understanding in-memory MapReduce, Interactive operations on MapReduce, Spark stack, fine vs. Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting r2, adjusted r2, mean squared error, etc.Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model.Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.K-means – The K-means an algorithm that can be used for clustering problems in an unsupervised learning approach.Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.How to optimize the efficiency of the clustering model?.How to evaluate the model for a clustering problem?.How to train the model in a clustering problem?.Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
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