At first 7 days, I have worked on practicing the general dataset manipulations:
- Importing the Dataset from various sources
- Describing the Dataset
- Dealing with the Missing Values
- Dealing with the Outliers
- Visualizing the dataset.
All the Python notebooks can be found at my github via the link below:
Episode 2: The Nucleus.
In next 14 days, two main libraries of Python will be explored:
Pandas (Day 8 – Day 14)
Pandas is the main data manipulation and data analysis package for Python. There are many useful Pandas functions that are heavily used in the pre-processing step. Therefore, it is necessary to learn it more in depth.
In order to make the learning process more measurable, I will follow few challenges presented online. I will start with the Pandas Challenge provided by Guilherme at the below link:
Once I am done with it, I will follow more with the below links:
Numpy (Day 15 – Day 21)
Numpy is the core package for numerical computations. Since AI/ML is strongly math based, it makes sense to learn the package in depth at the beginning.
To learn Numpy, I will use a Numpy 100 challenge provided by Nicolas at below link:
Once I am done with 100 questions there, I will follow with the other sources below:
Show Must Go On…