Machine Learning instructional classes show through hands-on training how to apply machine learning systems and devices for taking care of certifiable issues in different businesses. NobleProg ML courses cover distinctive programming dialects and structures, including Python, R dialect and Matlab. Machine Learning courses are offered for various industry applications, including Finance, Banking and Insurance and cover the essentials of Machine Learning and additionally further developed methodologies, for example, Deep Learning. Machine Learning preparing is accessible as “on location live preparing” or “remote live preparing”. On location live preparing can be done locally on client premises in Hyderabad or in NobleProg corporate instructional hubs in Hyderabad. Remote live preparing is completed by method for an intelligent, remote work area. NobleProg – Your Local Training Provider.


Machine Learning in Data Science

Deploying machine learning for data analysis, solving business problems, using algorithms for searching patterns in data, relationship between variables, multivariate analysis, interpreting correlation, negative correlation.

Deep dive into Data Transformation

Data Transformation key phases Data Mapping and Code Generation, Data Processing operation, data patterns, data sampling, sampling distribution, normal and continuous variable, data extrapolation, regression, linear regression model.

Data Testing and Assessment

Data analysis, hypothesis testing, simple linear regression, Chi-square for assessing compatibility between theoretical and observed data, implementing data testing on data warehouse, validating data, checking for accuracy, data operational monitoring capabilities.

Data Model, Algorithms & Prediction

Various techniques of data modelling and generating algorithms, methods of business prediction, prediction approaches, data sampling, disproportionate sampling, data modelling rules, data iteration, and deploying data for mission-critical applications.

Data Segmentation and Analysis

Working with large data sets in data warehouses, data clustering, grouping, horizontal & vertical slicing, data sharding in partitioning, clustering algorithms, K-means Clustering for analysis and data mining, exclusive clustering, hierarchy clustering, Mahout Clustering algorithm and Probabilistic Clustering, nearest neighbour search, pattern recognition, and statistical classification.


GPS INFOTECH (Software Solutions)
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