Here you can get some important big data topics in which you can get help.
Boston House Prediction
Big Data - Boston Data Set Regression and Classification
Big Data Using PySpark Using Twit Dataset
Download tweets data from https://www.kaggle.com/kazanova/sentiment140
The data is colossal. It contains 16,00,000 tweets.
Perform the sentiment analysis using pyspark.
Build K-means Clustering Using "Wholesale customers data"
Data is about annual spending on different product categories of a wholesale distributor Build a K-means model to segment them based on spending.
Build Naive Byes Model Using "IRIS" Dataset
Build a Naive Byes Model to classify the species of IRIS flower
Build H Cluster Model Using "mtcars" Dataset
With the help of H Cluster model to segment cars model based on specification data
Build PCA Model To Reduce Dimensionality Using "malignant_benign" Dataset
With the help of PCA reduce the dimensionality for building model to predict whether the tissues is malignant or benign.
Build Random Forest & GBM Model Using "mushrooms" Dataset
With the help of Random forest & GBM predict whether a given mushrooms is edible or poisonous to human beings. Dataset has got 8124 observations & 23 variables.
Build PCA Model To Reduce Dimensionality Using "mushrooms" Dataset
With the help of PCA reduce the dimensionality for building a model to predict whether a given mushrooms is edible or poisonous to human beings. Dataset has got 8124 observations & 23 variables.
Reduce Dimensionality with Factor Analysis using "malignant_benign " Dataset
With the help of Factor Analysis for assessing the association of the variables with each factor.
Building H Cluster Model using "Protein" Dataset
With the help of H Cluster Model to segment countries based on protein consumption.
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