Exercise 3: Solution
The course is part of this learning path
Learn the ways in which data comes in many forms and formats with the second course in the Data and Machine Learning series.
Traditionally, machine learning has worked really well with structured data but is not as efficient in solving problems with unstructured data. Deep learning works very well with both structured and unstructured data, and it has had successes in fields like translation, and image classification, and many others. Learn and study how to explain the reasons deep learning is so popular. With many different data types, learn about its different formats, and we'll analyze the vital libraries that allow us to explore and organize data.
This course is made up of 8 lectures, accompanied by 5 engaging exercises along with their solutions. This course is part of the Data and Machine Learning learning paths from Cloud Academy.
- Learn and understand the functions of machine learning when confronted with structured and unstructured data
- Be able to explain the importance of deep learning
- It would be recommended to complete the Introduction to Data and Machine Learning course, before starting.
Hey guys, welcome back! Let's go on to exercise three. We solve exercise three by plotting the histogram of the height of males and the height of females. We have these from the previous exercise so we don't need to recreate them. We just need to set the parameters of the histograms and here it's important to choose the same parameters, so the same range, the same number of bins so that the two histograms can be compared. Then we set the title, we set the legend, and we set the x-axis label.
And finally, we set, we draw two vertical lines using the ax v for vertical line, one at the mean height of males in blue and another one at the mean height of females in red. So if I execute this whole cell, what I see, is this beautiful double histogram for the males and the females with their respective mean heights. I could have done this also in this way, this is the cumulative distribution. Notice that I've set cumulative true and normed equal to true, and here I've set a few horizontal lines using the ax h line. This is not really requested but I thought it was cool to show you anyway. So thank you for watching and see you in the next video.
I am a Data Science consultant and trainer. With Catalit I help companies acquire skills and knowledge in data science and harness machine learning and deep learning to reach their goals. With Data Weekends I train people in machine learning, deep learning and big data analytics. I served as lead instructor in Data Science at General Assembly and The Data Incubator and I was Chief Data Officer and co-founder at Spire, a Y-Combinator-backed startup that invented the first consumer wearable device capable of continuously tracking respiration and activity. I earned a joint PhD in biophysics at University of Padua and Université de Paris VI and graduated from Singularity University summer program of 2011.