Data Science and Machine Learning

Data Science and Machine Learning Tutorials
Such as NLP,ML,DL,AI and more

An Intro to DagsHub For Data Scientists

DagsHub is a platform for data scientists and machine learning engineers to version their data, models, experiments, and code. In a way it is like Github for Data Scientists and ML Engineers. It is where Data Scientists build their ML projects without any external and complicated devops. It seeks to simplify MLOps for everyone. It allows …

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Hash Identification Using Machine Learning and 3 Tools

A hash is unique fixed-size values or a fixed-length string of characters produced by a hash function. It is the values returned by a hash algorithm. Such values can also be termed as Message Digests or simply a Hash. A hash function is any function than can be used to map data of arbitrary size …

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Natural Language Processing with Spark NLU

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 …

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Streamlit Projects – An App Challenge Series

In this series of post we will be building several web applications using Streamlit. The plethora of apps we will be building will range from simple fun and useful apps to complex data science apps. Our main framework will be streamlit. So what is streamlit? Streamlit is a powerful framework for build data apps as …

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How to Programmatically Label Datasets using Snorkel in Python

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 …

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How to Visualize Neural Networks

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 …

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Data Analysis with JavaScript Using Data-Forge

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 …

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Online Machine Learning In Python with River (ML on Streaming Data)

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 …

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How to Set a Baseline for Machine Learning Models in Python

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 …

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streamlit themes

Streamlit Themes – How to Customize Your Streamlit Apps

Streamlit has done it again, it has introduced a long awaited feature request – Themes. The ability to change the look of streamlit apps is now possible with the Streamlit Themes. To enjoy this feature you will need to update your streamlit to version 0.79 and upwards pip install –upgrade streamlit Streamlit Themes The new …

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