Chawla

Why I stopped using the merge method in Pandas and why you should tooPhoto by Alain Pham on UnsplashThe merge() method in Pandas is undoubtedly among the most frequently used methods by data scientists in their data science projects.Derived from the idea of table joins in SQL and extended to joining tables in a pythonic environment, the method merges two Pandas DataFrames based on the matching values in one or more columns.This is illustrated in the diagram below:Diagrammatic Overview of joining tables (Image by…

Precision and Recall elaborated with sample situationsPhoto by Afif Kusuma on Unsplash· Introduction· Precision and Recall· Precision∘ Understanding the Precision Mindset· Recall∘ Understanding the Recall Mindset· Precision vs Recall· ConclusionUtilizing the right set of evaluation metrics to estimate the performance of a data-driven classification model holds immense importance in building and delivering a reliable machine learning solution/product.As the name suggests, classification models are a category of machine…

A Comprehensive Guide to Pytest for Data Science ProjectsPhoto by Annie Spratt on UnsplashOne of the biggest hurdles today’s data science teams are facing is transitioning their data-driven pipeline from jupyter notebooks to executable, reproducible, and organized files comprising functions and classes.For most of us, working in a jupyter notebook is a fun and enjoyable task in the life-cycle of a data science project.However, building an error-free, well-tested, and reliable data pipeline that does not break in…

A guide to generating a List, a Dictionary, and a NumPy array from Pandas DataFramePhoto by Chris Lawton on UnsplashThe Pandas DataFrames have been widely popular among Machine Learning Engineers and Data Scientists for various tabular data analysis, management, and processing tasks.Tabular data with three columns and three rows (Image by Author)While the Pandas library is self-sufficient for numerous use-cases and various other Python libraries provide inherent support for Pandas such as Matplotlib, Plotly, Sklearn,…

Analyze your audio file in a single placePhoto by Kelly Sikkema on UnsplashLanguage forms the basis of every conversation between humans. Due to this, the field of Natural Language Processing (or NLP for short) undoubtedly holds immense potential in assisting humans with their day-to-day lives.In simple words, the domain of NLP comprises a set of techniques that aim to comprehend human language data and accomplish a downstream task.NLP techniques encompass numerous areas such as Question Answering (QA), Named Entity…

Building a web app that talks to GPT-3Photo by Soundtrap on UnsplashLarge Language Models (LLMs for short), such as PaLM by Google, GPT-3 by OpenAI, Megatron-Turing NLG by Microsoft-NVIDIA, etc., have achieved remarkable performance in generating comprehensive natural language texts.Contemporarily, among these three models, only OpenAI’s GPT-3 is available to the public, with accessibility using OpenAI’s APIs. As a result, since its release, OpenAI’s GPT-3 has been leveraged in over 300 applications/products. (source:…

Hush Hush trailer is here. Amazon Prime Video has released the first trailer for its upcoming Juhi Chawla-led dramatic thriller. The seven-episode series follows a group of middle-aged women, whose picture-perfect lives begin to unravel when an unforeseen event intervenes. Tanuja Chandra — best known for the Irrfan Khan-led Qarib Qarib Singlle — directs the show from a scribe by Shikhaa Sharma, who previously worked on Amazon's Sherni. Hush Hush premieres September 22, exclusively on Prime Video.The Hush Hush trailer…

Don’t just train, but also deploy: a step-by-step guidePhoto by Roman Synkevych on UnsplashBuilding and deploying data-driven intelligent systems at scale has been of great interest lately to organizations operating in the machine learning space. This has not only led to the rapid evolution of efficient and accurate systems but has also had a profound contribution in improving the overall end-user experience by using intelligence-embedded products.Due to the various benefits associated with intelligence-embedded software,…

A comprehensive guide to creating NumPy arraysPhoto by Vardan Papikyan on UnsplashThe NumPy library in Python forms the fundamental building blocks of almost every Data Science and Machine Learning project today.Due to its immense potential in supporting vectorized operations and processing large amounts of numerical data efficiently, it has become one of the most important libraries ever built in Python.Moreover, the whole data-driven ecosystem is in some way or the other dependent upon NumPy and its core…

Discussing five subtle limitations of PandasPhoto by Georg Bommeli on UnsplashThanks to the Pandas library, handling, analyzing, and processing tabular data in Python has never been as effortless and straightforward as it is today.Contemporarily, the Pandas API provides an extensive collection of functionalities to manage tabular data, intending to serve almost every data science project, such as:Input and Output operationsData FilteringTable JoinsData visualizationDuplicate data handling, and many more, which you can…