Evaluation Metrics for Classification Problems
Author(s): Edward Ma Why metrics need to be defined at the very beginning Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
30+ Data Science Interview Questions from FAANG Tech Giants
Author(s): Terence S In-depth Interview Q&A from Facebook, Amazon, Apple, Netflix, and Google Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Combine datasets using Pandas merge(), join(), concat() and append()
Author(s): Vivek Chaudhary Source: Pexels In the world of Data Bases, Joins and Unions are the most critical and frequently performed operations. Almost every other query is an amalgamation of either a join or a union. Using Pandas we perform similar kinds …
4 Pathways to Data Science
Author(s): Benjamin Obi Tayo Ph.D. It is never too late to jump into data. These pathways can help you gain the essential skills for data science practice. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Getting Started with Kaggle Competitions Using Monk AI
Author(s): sinchana S.R Deep Learning Monk is a low code deep learning tool and a suitable wrapper for computer vision. Monk Features Low-code. Unified wrapper over major deep learning framework s — Keras, PyTorch, gluoncv. Syntax invariant wrapper. Monk Enables To create, manage, and version control …
Jupyter Notebook for Data Science Coding Exercise
Author(s): Benjamin Obi Tayo Ph.D. Some coding challenge problems would specify that a formal project report be submitted together with a Jupyter notebook or R Script file Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Bayes’ Theorem Explained
Author(s): Benjamin Obi Tayo Ph.D. Bayes’ theorem is crucial for interpreting the results from binary classification algorithms, and a most know for aspiring data scientists Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Five Cool Python Libraries for Data Science
Author(s): Dhilip Subramanian Handy Python libraries for data science Python is a best friend for the majority of the Data Scientists. Libraries make their life simpler. I have come across five cool Python libraries while working on my NLP project. This helped me …
How, When, and Why Should You Normalize / Standardize / Rescale Your Data?
Author(s): Swetha Lakshmanan Before diving into this topic, lets first start with some definitions. “Rescaling” a vector means to add or subtract a constant and then multiply or divide by a constant, as you would do to change the units of measurement …
The Best Public Datasets for Machine Learning and Data Science
Author(s): Stacy Stanford, Roberto Iriondo, Pratik Shukla Best Public Datasets for Machine Learning and Data Science Best open-access datasets for machine learning, data science, sentiment analysis, computer vision, natural language processing (NLP), clinical data, and others. This resource is continuously updated. If you …
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