Reading Time: 3 minutes Introduction to Mako Have you ever worked on a project in Python and thought to yourself, “Gee, it would be nice if I could dynamically generate web pages and/or text and have them directly interact with my program.” Well, you’re in luck because enter Mako templates. Mako is a template library and a Python Sever Page language, allowing content such as HTML, XML, and text Continue Reading
Reading Time: 2 minutes Introduction Marshmallow, stylized as “marshmallow”, is an object-relational mapping library which is used to convert objects to and from Python data types. It is often used alongside SQLAlchemy, an ORM that maps database schemas to Python objects. Marshmallow is often used to deserialize Python dicts to SQLAlchemy models and vice versa. Let’s focus on how to use Marshmallow. Creating Schemas First, we need to create Continue Reading
Reading Time: 3 minutes In this blog, we are going to run the sample dynamic DAG using docker. Before that, let’s get a quick idea about the airflow and some of its terms. What is Airflow? Airflow is a workflow engine which is responsible for managing and scheduling running jobs and data pipelines. It ensures that the jobs are ordered correctly based on dependencies and also manages the allocation Continue Reading
Reading Time: 3 minutes In this blog, we will see how to make our machine learning model’s prediction faster with a recently open-sourced library Hummingbird. Nowadays, we can see a lot of frameworks for deploying or serving the machine learning model into production. As a result, It is a headache for a data scientist to choose between these frameworks, keeping in mind how their model either Sklearn or LightGBM Continue Reading
Reading Time: 4 minutes NumPy’s built-in methods and concepts like vectorization, broadcasting and indexing allows you to focus on answering questions from your data and not about how to code those solutions. NumPy handles most of that for you.
Reading Time: 7 minutes In this blog, we are going to see some basic text operations with NLP, to solve different problems. This Blog is a part of a series Ultimate guide to NLP , which will focus on Basic text pre-processing techniques. Some of the major areas that we will be covering in this series of Blogs include the following: Text Pre-Processing Understanding of Text & Feature Engineering Continue Reading
Reading Time: 5 minutes In this blog, we are going to see how XGBoost works and some of the important features of XGBoost with the help of an example. So, many of us heard about tree models and boosting techniques. Let’s put these concepts together and talk about XGBoost, the most powerful machine learning Algorithm out there. XGboost called for eXtreme Gradient Boosted trees. The name XGBoost, though, actually Continue Reading
Reading Time: 7 minutes In this blog, we are going to see how we can Anticipate customer behavior with Market Basket analysis By using Association rules. Introduction to Market Basket analysis Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in transactions. To put it another way, it Continue Reading
Reading Time: 7 minutes Introduction Python is a great flexible programming language that can be used in many situations. In this tutorial, we will focus primarily on it’s ability to enhance the Unix/Linux shell environment. Typically in Unix we will create “bash” shell scripts, but we can also create shell scripts using python, and it’s really simple! We can even name our shell scripts with the .sh extension and Continue Reading
Reading Time: 3 minutes In our previous blog Introduction to Django, we discussed the Django’s features and architecture. In this blog, we will create a web application in Django. For starting a new project, go to the folder where you want your project to be and run the command: django-admin startproject django_proj django-admin Django’s command-line utility for administrative tasks.manage.py is automatically created in each Django project. manage.py does the Continue Reading
Reading Time: 4 minutes In this blog, we are going to go through about one of the widely used classification algorithm called KNN (K-Nearest Neighbors). Since I started doing data science, I observed that most of the problems end up with classification model The main reason behind this biased property is, most of the analytic problems are based on decision making. For instance, to identify loan applicants as low, Continue Reading
Reading Time: 3 minutes In this blog, we are going to talk about Django. Before that let’s understand what is web framework and why do we need it? A web framework is a software tool that helps us develop application faster and smarter. It eliminates the need to write a lot of repetitive code and saves time. What is Django? Django is a free open source high-level web framework Continue Reading
Reading Time: 8 minutes In this Blog, we are going to learn about how to do Data Cleaning in Python. Most data scientists spend only 20 percent of their time on actual data analysis and 80 percent of their time finding, cleaning, and reorganizing huge amounts of data, which is an inefficient data strategy. The reason data scientists are hired in the first place is to develop algorithms and Continue Reading
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