Bokeh is a Python package that helps in data visualization. It is an open source project. Bokeh renders its plot using HTML and JavaScript. This indicates that it is useful while working with web−based dashboards.Bokeh converts the data source into a JSON file. This file is used as an input to BokehJS, which is a JavaScript library. This BokehJS is written in TypeScript that helps render visualization on modern browsers.Matplotlib and Seaborn produce static plots, whereas Bokeh produces interactive plots. This means when the user interacts with these plots, they change accordingly.Dependencies of Bokeh −Numpy Pillow Jinja2 Packaging Pyyaml Six ... Read More

Bokeh is a Python package that helps in data visualization. It is an open source project. Bokeh renders its plot using HTML and JavaScript. This indicates that it is useful while working with web-based dashboards.Bokeh converts the data source into a JSON file. This file is used as an input to BokehJS, which is a JavaScript library. This BokehJS is written in TypeScript that helps render visualization on modern browsers.Matplotlib and Seaborn produce static plots, whereas Bokeh produces interactive plots. This means when the user interacts with these plots, they change accordingly.Plots can be embedded as output of Flask or ... Read More

Matplotlib library is built upon Numpy. It is a Python library that is used to visualize data. It is a tree-like hierarchical structure which consists of objects that makeup each of these plots. A ’Figure’ in Matplotlib can be understood as the outermost storage for a graph. This ‘Figure’ can contains multiple ‘Axes’ objects. ‘Axes’ object is NOT the plural form of ‘Axis’ in this case.‘Axes’ can be understood as a part of ‘Figure’, a subplot. It can be used to manipulate every part of the graph inside it. A ‘Figure’ object in Matplotlib is a box that stores one ... Read More

Matplotlib library is built upon Numpy. It is a Python library that is used to visualize data. It is a tree−like hierarchical structure which consists of objects that makeup each of these plots.A ’Figure’ in Matplotlib can be understood as the outermost storage for a graph. This ‘Figure’ can contains multiple ‘Axes’ objects. ‘Axes’ object is NOT the plural form of ‘Axis’ in this case.‘Axes’ can be understood as a part of ‘Figure’, a subplot. It can be used to manipulate every part of the graph inside it. A ‘Figure’ object in Matplotlib is a box that stores one or ... Read More

Bokeh is a Python package that helps in data visualization. It is an open source project. Bokeh renders its plot using HTML and JavaScript. This indicates that it is useful while working with web-based dashboards.Bokeh can be easily used in conjunction with NumPy, Pandas, and other Python packages. It can be used to produce interactive plots, dashboards, and so on.Matplotlib and Seaborn produce static plots, whereas Bokeh produces interactive plots. This means when the user interacts with these plots, they change accordingly.Plots can be embedded as output of Flask or Django enabled web applications. Jupyter notebook can also be used ... Read More

Bokeh is a Python package that helps in data visualization. It is an open source project. Bokeh renders its plot using HTML and JavaScript. This indicates that it is useful while working with web-based dashboards.Bokeh can be easily used in conjunction with NumPy, Pandas, and other Python packages. It can be used to produce interactive plots, dashboards, and so on. It helps in communicating the quantitative insights to the audience effectively.Matplotlib and Seaborn produce static plots, whereas Bokeh produces interactive plots. This means when the user interacts with these plots, they change accordingly.Plots can be embedded as output of Flask ... Read More

Time series, as the name suggests, is data that contains certain time periods or time stamps. It contains observations over certain time period. This kind of data tells us about how variables change over time based on various factors. Time series analysing and forecasting can be used to predict data with respect to some future time.Univariate time series contains values taken with respect to a single variable at certain time instances over a period of time. A multivariate time series contains values taken with respect to multiple variables at same periodic instances of time.Time series consists of 4 components that ... Read More

Scikit−learn, commonly known as sklearn is a library in Python that is used for the purpose of implementing machine learning algorithms. It is an open-source library hence it can be used free of cost. It is powerful and robust, since it provides a wide variety of tools to perform statistical modelling. This includes classification, regression, clustering, dimensionality reduction, and much more with the help of a powerful, and stable interface in Python. The library is built on Numpy, SciPy and Matplotlib libraries.It can be installed using the ‘pip’ command as shown below −pip install scikit−learnThis library focuses on data modelling. ... Read More

Scikit−learn, commonly known as sklearn is a library in Python that is used for the purpose of implementing machine learning algorithms. It is an open−source library hence it can be used free of cost.It is powerful and robust, since it provides a wide variety of tools to perform statistical modelling. This includes classification, regression, clustering, dimensionality reduction, and much more with the help of a powerful, and stable interface in Python.This library is built on Numpy, SciPy and Matplotlib libraries.It can be installed using the ‘pip’ command as shown below −pip install scikit−learnThis library focuses on data modelling.The streamlining operation ... Read More

The idea behind using gradient descent is to minimize the loss when in various machine learning algorithms. Mathematically speaking, the local minimum of a function is obtained.To implement this, a set of parameters are defined, and they need to be minimized. Once the parameters are assigned coefficients, the error or loss is calculated. Next, the weights are updated to ensure that the error is minimized. Instead of parameters, weak learners can be users, such as decision trees.Once the loss is calculated, gradient descent is performed, and tree is added to the algorithm step wise, so that loss is minimal.Some examples ... Read More