MP4 | Video: AVC 916x514 30 fps | Audio: AAC 44.1 KHz 2ch | Duration: 2h 51m
Genre: eLearning | Language: English | Size: 418 MB
Introducing Data Visualization and Line Plots.
Be able to explain data visualization in the context of big data, and create line plots using the Python Matplotlib library in this first topic in the Data Science and Machine Learning Series. Know the five stages in the data science pipeline: understanding the problem statement, acquiring data and cleaning the data, data visualization and exploratory analysis, creating machine learning models that make predictions, and sharing the results and visualizing them. Install the Matplotlib library and numpy which will be used during this course, and create several interesting line plots.
Creating Scatter Plots and Bar Graphs using Python and Matplotlib. Create scatter plots and bar graphs using Python and Matplotlib in this second topic in the Data Science and Machine Learning Series. Follow along with Advait as he shows you how to debug as well.
Creating Pie Charts using Python and Matplotlib. Create pie charts using Python and Matplotlib in this third topic in the Data Science and Machine Learning Series.
Using Normal Distributions and Histograms in Python and Matplotlib. Use normal distributions and create histograms using Python and Matplotlib in this fourth topic in the Data Science and Machine Learning Series. A normal distribution is a bell curve where the x-axis denotes a random variable X and the y-axis denotes the probability of occurrence of that X.
The Movie Data Visualization Project. Reinforce your data visualization skills by creating a full visualization project using Python, Numpy, and Matplotlib on the subject of movies in this fifth topic in the Data Science and Machine Learning Series.
Performing Data Visualization using the Python Bokeh Library. Perform data visualization using Bokeh Library in this sixth topic in the Data Science and Machine Learning Series. Create an interactive histogram using this powerful Python library.
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