Mısra Turp

Hello friends,

This is my course Hands-on Data Science which was released back in 2020 to help aspiring data scientists learn how the end-to-end process of a data science project works. It has been a paid course since it was published but now I believe it is time for it to be publicly accessible.

I will publish the course lessons as soon as I get them ready for YouTube. So keep an eye out for the new lessons every week!

Best,
Mısra

1 year ago | [YT] | 13

Mısra Turp

Hey friends!

My channel has been silent lately but it doesn't mean I stopped making videos. Take a look at AssemblyAI's channel to see other videos from me. :)

Here is the latest one 👇

2 years ago | [YT] | 8

Mısra Turp

Deepfakes: are they dangerous or only a fun filter to use on social media? Probably both. In this video, I discuss the benefits and potential dangers of the deepfake technology and show you how I made a voice clone of myself using an app called Descript and 10 minutes of me talking.

2 years ago | [YT] | 7

Mısra Turp

Recently, I had the chance to sit down with Chanin Nantasenamat also known on YouTube as  @DataProfessor  and have a nice chat! We talked about his background, how he decided to start his YouTube channel, how he built his YouTube channel to the size it is now, what future plans he has, his role at Streamlit and advice he can give to aspiring data science practitioners.

2 years ago | [YT] | 6

Mısra Turp

Streamlit has this awesome service where you can deploy and host your Sreamlit apps with just a couple of clicks from your GitHub repo. But while building with Streamlit, we sometimes use APIs or other online services to enrich our web app. If you upload your code to GitHub without hiding your API keys and passwords anyone can get access to them and use your personal keys to access these services.

To avoid this, we need to hide our API keys and password that are used in the application. Luckily Streamlit Share has a very neat way of doing this. Let's see it in this quick video!

2 years ago | [YT] | 8

Mısra Turp

Streamlit is a Data Scientist favorite when it comes to building web apps for our projects. It has many different widgets, components and functionalities within itself. Here are my 9 favorite Streamlit elements and components that I love to use.

2 years ago | [YT] | 7

Mısra Turp

The GroupBy function is sometimes confusing and overwhelming for people who are just starting with programming in pandas, or even for people who have been using pandas for years. In this tutorial, I will show you the ins and outs of the groupby function, how to use it, what it returns and how to deal with the groups that are created.

There is also an introduction for a little bonus function at the end that I think will be very useful for you called the pd.Grouper.

2 years ago | [YT] | 7

Mısra Turp

While cleaning up outliers, filling in missing values, or just doing some data maintenance we need to update the values in our Pandas dataframe. Sometimes you select a subset of the original dataframe, and sometimes it needs to be pinpointed with an index value. So in this video, I show you every way I know how to replace and/or modify values in your pandas dataframes.

2 years ago | [YT] | 5

Mısra Turp

When working with datasets you will need to change the shape and the perspective of the data. This is done sometimes for analysis purposes and sometimes just to explore the data a bit better. In this video, we learn 8 ways to change the shape of the dataframe we are working with to gain a new perspective on it. The functions we learn are:

1. pivot
2. pivot_table
3. Stack
4. Unstack
5. Melt
6. Groupby
7. Crosstab
8. Explode

2 years ago | [YT] | 10

Mısra Turp

Pandas map, apply and applymap functions work in a similar way but the effect they have on the dataframe is slightly different. Today we will look closely into how each function works and the differences they have from each other.

You can find the code and the dataset here: github.com/misraturp/Pandas-apply-vs.-map-vs.-appl…

2 years ago | [YT] | 13