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Data Modeling using Tensorflow
Data Modeling using Tensorflow
Tensorflow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data. TFF has been developed to facilitate open research and experimentation with Federated Learning (FL), an approach to machine learning where a shared global model is trained across many participating clients that keep their training data locally
An end-to-end open source machine learning platform
Advantages
Advantages
ML Problems
ML Problems
Basic Problems occured while working with Tensorflow
Basic Problems occured while working with Tensorflow
tf.random.set_seed(seed) instead of tf.set_random_seed(seed)
Notations
Notations
Let’s annotate this on the plot using the annotate method of the scripting layer or the pyplot interface. We will pass in the following parameters:
s: str, the text of annotation.
xy: Tuple specifying the (x,y) point to annotate (in this case, end point of arrow).
xytext: Tuple specifying the (x,y) point to place the text (in this case, start point of arrow).
xycoords: The coordinate system that xy is given in – ‘data’ uses the coordinate system of the object being annotated (default).
arrowprops: Takes a dictionary of properties to draw the arrow:
arrowstyle: Specifies the arrow style, '->' is standard arrow.
connectionstyle: Specifies the connection type. arc3 is a straight line.
color: Specify color of arrow.
lw: Specifies the line width.
About Subplot Creation
About Subplot Creation
nrows and ncols are used to notionally split the figure into (nrows * ncols) sub-axes,
plot_number is used to identify the particular subplot that this function is to create within the notional grid. plot_number starts at 1, increments across rows first and has a maximum of nrows* ncols as shown below.
plot_number is used to identify the particular subplot that this function is to create within the notional grid. plot_number starts at 1, increments across rows first and has a maximum of nrows* ncols as shown below.
Often times we might want to plot multiple plots within the same figure. For example, we might want to perform a side by side comparison of the box plot with the line plot of China and India’s immigration.
To visualize multiple plots together, we can create a figure (overall canvas) and divide it into subplots, each containing a plot. With subplots, we usually work with the artist layer instead of the scripting layer.
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