Natural Language Processing ( NLP for short) is an exciting and useful field of Data Science. Some of applications of NLP involves Text Classification Sentiment Analysis Machine Translation Chatbots Creation Keyword Extraction NER etc With the increase of textual data, comes the increase of performant and fine tuned State of the Art(SoTA) models. These models …
Julia is an exciting and fascinating programming language like Python and R and Go. It offers several benefit if you are into scientific computing and Datascience. In this tutorial we will explore how to develop and publish Julia Packages. We will using this simple workflow for designing our package. This describes everything that we will …
How to Develop and Publish Julia Packages For Beginners Read More »
Machine Learning can be grouped into two based on the presence or absence of labels or target class. This gives us the main branches of supervised machine learning (where the dataset is provided with predefined labels) and unsupervised machine learning (where there are no labels given). The task of assigning labels to a dataset is …
How to Programmatically Label Datasets using Snorkel in Python Read More »
Documentations are essential for building softwares, in fact documentation is also part of the software you design and develop. It is what differentiate a good software from not a good one. In this tutorial we will be learning how to use a nice library called mkdocs to generate documentations for our software project. As the …
Neural Networks or preferably called Artificial neural networks forms the building block for Deep learning activities. In this article, we will explore the various ways we can visualize your neural network architecture. We will be using 4 different methods to help us visualize the components of a neural network. By the end of this tutorial …
Python is popular in the data science world. It has several libraries and packages for performing data analysis, data visualization, machine learning,deep learning and also for converting your models into product. Certain libraries like Pandas, Scikit-learn, Tensorflow, PyTorch, Flask, Streamlit and Plotly made Python very useful for Data Scientist and Data Engineers. JavaScript on the …
All programming languages can be classified under two main groups based on how and when we assign data-types to variables before the program runs. In this respect there can be static typed programming languages such as Java, C++ ,Go and dynamic typed programming languages such as Python, JavaScript, Julia. However certain languages offers the freedom …
Introduction to Python Typing For Type Annotation Read More »
QR-code s a type of matrix barcode mostly 2-dimenstional barcode that was invented in 1994 by Denso Wave a Japanese automotive company. It stands for Qucik Response code. In this tutorial we will explore how to generate our own QR-code using python and also how to decode the generated QR-code. By the end of this …
The usual machine learning we perform is usually on data that is at rest, in other words we train our model on an already collected data which is in batches. This concept of building ML models on data at rest is termed Batch Machine Learning. It is the most common and useful. However what if …
Online Machine Learning In Python with River (ML on Streaming Data) Read More »
When building machine learning models, it is essential to have a baseline by which you can compare the performance of the model you are building. The baseline you set gives you the benefit of knowing whether you are on track and whether your model is improving or not. The type of baseline you set is …
How to Set a Baseline for Machine Learning Models in Python Read More »