Snells introduction to probability

List snells introduction to probability

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    course content

    introduction to python
    basic steps
    numpy
    data visualization
    pandas
    exceptions and errors
    introduction to artificial intelligence and machine learning
    data wrangling and manipulation
    supervised learning
    supervised learning-classification
    unsupervised learning
    machine learning pipeline building
    decision tree analysis and ensemble learning
    ai and deep learning introduction
    artificial neural network
    deep neural network & tools
    deep neural net optimization, tuning, interpretability
    convolutional neural net
    recurrent neural networks
    overfit and underfit
    transfer learning
    working with generative adversarial networks
    pytorch

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  • In 360digitmgthis data science course begins with an introduction to statistics, probability, python and r programming and exploratory data analysisdata mining unsupervised using clustering, dimension reduction and association rules is also dealt with in detaillearn to perform proactive forecasting and time series analysis with algorithms scripted in python and r in the best data science training institute in chennaiparticipants learn to perform data mining supervised with linear regression and predictive modelling with multiple linear regression techniquesa module is dedicated to scripting machine learning algorithms and enabling deep learning and neural networks with black box techniques and svm

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  • probability, random variables and random signal principles by peyton z peebles jr

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  • Eduwiser's probability for iit-jee book

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  • A text book of probability by sinha

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  • A first course in probability sixth editon by sheldon ross book

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