Python for Machine Learning Crash Course. Learn core Python in 7 days. Python is an amazing programming language. Not only it is widely used in machine learning projects, you can also find its presence in system tools, web projects, and many others. Having good Python skills can make you work more efficiently because it is […]
Archive | Python for Machine Learning
Developing a Python Program Using Inspection Tools
Python is an interpreting language. It means there is an interpreter to run our program, rather than compiling the code and running natively. In Python, a REPL (read-eval-print loop) can run commands line by line. Together with some inspection tools provided by Python, it helps to develop codes. In the following, you will see how […]
Monkey Patching Python Code
Python is a dynamic scripting language. Not only does it have a dynamic type system where a variable can be assigned to one type first and changed later, but its object model is also dynamic. This allows us to modify its behavior at run time. A consequence of this is the possibility of monkey patching. […]
Logging in Python
Logging is a way to store information about your script and track events that occur. When writing any complex script in Python, logging is essential for debugging software as you develop it. Without logging, finding the source of a problem in your code may be extremely time consuming. After completing this tutorial, you will know: […]
Profiling Python Code
Profiling is a technique to figure out how time is spent in a program. With these statistics, we can find the “hot spot” of a program and think about ways of improvement. Sometimes, a hot spot in an unexpected location may hint at a bug in the program as well. In this tutorial, we will […]
Static Analyzers in Python
Static analyzers are tools that help you check your code without really running your code. The most basic form of static analyzers is the syntax highlighters in your favorite editors. If you need to compile your code (say, in C++), your compiler, such as LLVM, may also provide some static analyzer functions to warn you […]
Setting Breakpoints and Exception Hooks in Python
There are different ways of debugging code in Python, one of which is to introduce breakpoints into the code at points where one would like to invoke a Python debugger. The statements used to enter a debugging session at different call sites depend on the version of the Python interpreter that one is working with, […]
Using Kaggle in Machine Learning Projects
You’ve probably heard of Kaggle data science competitions, but did you know that Kaggle has many other features that can help you with your next machine learning project? For people looking for datasets for their next machine learning project, Kaggle allows you to access public datasets by others and share your own datasets. For those […]
Techniques to Write Better Python Code
We write a program to solve a problem or make a tool that we can repeatedly solve a similar problem. For the latter, it is inevitable that we come back to revisit the program we wrote, or someone else is reusing the program we write. There is also a chance that we will encounter data […]
Google Colab for Machine Learning Projects
Have you ever wanted an easy-to-configure interactive environment to run your machine learning code that came with access to GPUs for free? Google Colab is the answer you’ve been looking for. It is a convenient and easy-to-use way to run Jupyter notebooks on the cloud, and their free version comes with some limited access to […]