Select the representations that do not change the location of the point a. [-2.-357) D. (-2,-²5) b. d Choose the representations below. Select all that apply. (2.-25) (-2,-35) 3 (-2,-²/²)
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- Many cement companies have research and development teams that continuously formulate and experiment different composition of chemicals to fully optimize the cement that they produce. Suppose a research team formulates 5 different mixtures every month. Two mixtures are selected at random from each batch for testing. The possible outcomes of the selection process are represented by pairs. For example, the pair (1, 2) represents the selection of mixtures 1 and 2 for testing. a. List all the different possible outcomes of the selection process. b. Suppose that mixtures 4 and 5 do not meet the requirements of the test. Two mixtures are to be chosen at random. Define ? to be the number of mixtures that does not meet the requirements among those tested. Find the probability distribution of ?. c. Find the cumulative distribution function of ?. Please answer this step by step and justify your answer.Perform gauss-jordan eliminationwe are going to use linear programming to develop a simple machinelearning algorithm to help us classify data points. Training data and Test data.Each of the 20 data points in the training data consists of 2 sensor readings x1, x2 whichare real numbers corresponding to the readout of two sensors during an event and a classi-cation y which is either 0 or 1, 0 indicates the event corresponding to the sensor data wasdetermined to not be a gravitational wave and a 1 indicates the event was determined tobe a gravitational wave. Thus, a typical line in the le looks something like:0.0 78.1 60.6Which indicates the 2 sensors had readings 78.1, 60.6 respectively, and the 0.0 indicatesno gravitational wave was observed. The test data consists again of sensor readings xi but with no classication y provided.Your job is to use the training data to develop a model that can take in sensor data andpredict the classication (again, 0 or 1). You will then run your model on the 20 points inthe test…
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