Tag Archives: Data Science
Using Theory of Change to Design Data-driven Solutions
Have you ever wanted to design a solution for an issue but weren’t sure how to do it? One theory that can help is the theory of change. The theory of change provides a framework for designing solutions by focusing on the steps needed to achieve desired outcomes or results. It also helps identify what needs to happen in order for the solution to be implemented successfully and realizing the desired outcomes. The theory of change when combined with data-driven decision making can result in great impact. In order to design solutions that have an impact and are sustainable, it is important to understand the theory of change as well …
Top 50 Interview Questions for Beginner Data Scientists
What interview questions should a beginner data scientist prepare for? This is an important question that many interviewees have. If you are going for a data scientist interview and don’t know what interview questions will you be asked, this blog post has some of the common interview questions that will help you excel in your interview. These interview questions are perfect for beginners because they cover basic topics about data science and machine learning and how it works. We hope this list helps! What is the difference between AI, machine learning, deep learning? Do you know how machine learning works? How is machine learning different from statistical modeling techniques like linear …
How to Create & Detect Deepfakes Using Deep Learning
Deepfake are becoming a more common occurrence in today’s world. What is deepfake and how can you create it using deep learning? This blog post will help data scientists learn techniques for creating and detecting deepfakes, so they can stay ahead of this technology. A deepfake is a video or audio that alters reality by changing the way something appears. For example, someone could place your face onto someone else’s body in a video to make it seem like you were there when you really weren’t. There are many ways that one can detect if a photo has been manipulated with software such as Photoshop or Gimp. What is deepfake? …
50+ Machine learning & Deep learning Youtube Courses
In this post, you get an access to curated list of 50+ Youtube courses on machine learning, deep learning, NLP, optimization, computer vision, statistical learning etc. You may want to bookmark this page for quick reference and access to these courses. This page will be updated from time-to-time. Enjoy learning! Course title Course type URL MIT 6.S192: Deep Learning for Art, Aesthetics, and Creativity Deep learning https://www.youtube.com/playlist?list=PLCpMvp7ftsnIbNwRnQJbDNRqO6qiN3EyH AutoML – Automated Machine Learning AutoML https://ki-campus.org/courses/automl-luh2021 Probabilistic Machine Learning Machine learning https://www.youtube.com/playlist?list=PL05umP7R6ij1tHaOFY96m5uX3J21a6yNd Geometric Deep Learning Geometric deep learning https://www.youtube.com/playlist?list=PLn2-dEmQeTfQ8YVuHBOvAhUlnIPYxkeu3 CS224W: Machine Learning with Graphs Machine learning https://www.youtube.com/playlist?list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn MIT 6.S897 Machine Learning for Healthcare Machine learning https://www.youtube.com/playlist?list=PLUl4u3cNGP60B0PQXVQyGNdCyCTDU1Q5j Deep Learning and Combinatorial Optimization Deep …
Online AI News from Top Global Universities – List
In this post, you will get an access to a list of web pages representing latest news related to artificial intelligence from top universities across the globe. This page will be updated from time-to-time for including new pages from different universities across the globe. These URLs will be very useful for those machine learning / data science enthusiasts who want to keep tab on current news and events in the field of artificial intelligence. MIT Stanford Stanford university – Human-centered AI (HAI) Stanford university – Center for AI in medicine and imaging Stanford AI research and ideas Harvard university JHU Malone center for Engg. in healthcare Yale university Princeton university …
MOSAIKS for creating Climate Change Models
In this post, you will learn about the framework, MOSAIKS (Multi-Task Observation using Satellite Imagery & Kitchen Sinks) which can be used to create machine learning linear regression models for climate change. Here is the list of few prediction use cases which has already been tested with MOSAIKS and found to have high model performance: Forest cover Elevation Population density Nighttime lights Income Road length Housing price Crop yields Poverty mapping What is MOSAIKS? MOSAIKS provides a set of features created from Satellite imagery dataset. We are talking about 90TB of data gathered per day from 700+ satellites. These features can be combined with machine learning algorithms to address global …
Machine Learning for predicting Ice Shelves Vulnerability
In this post, you will learn about usage of machine learning for predicting ice shelves vulnerability. Before getting into the details, lets understand what is ice shelves vulnerability and how it is impacting global warming / climate change. What are ice shelves? Ice shelves are permanent floating sheets of ice that connect to a landmass. Most of the world’s ice shelves hug the coast of Antarctica. Ice from enormous ice sheets slowly oozes into the sea through glaciers and ice streams. If the ocean is cold enough, that newly arrived ice doesn’t melt right away. Instead it may float on the surface and grow larger as glacial ice behind it continues to flow into the …
Top Data Sources for Climate Change Research
In this post, you will get to learn about top data sources online from where you can learn and get data for doing research on climate change. Vitalflux is committing itself to AI and climate change research for next 15 years. You will get to learn about climate change and how data science / machine learning can be leveraged to tackle climate change in time to come. Without further ado, lets list down the data sources related to climate change research: United Kingdom’s Met Office Hadley Centre: Researchers at the Met Office Hadley Centre produce and maintain a range of gridded datasets of meteorological variables for use in climate monitoring and climate …
Python – How to Create Dictionary using Pandas Series
In this post, you will learn about one of the important Pandas fundamental data structure namely Series and how it can be used as a dictionary. It will be useful for beginner data scientist to understand the concept of Pandas Series object. A dictionary is a structure that maps arbitrary keys to a set of arbitrary values. Pandas Series is a one-dimensional array of indexed data. It can be created using a list or an array. Pandas Series can be thought of as a special case of Python dictionary. It is a structure which maps typed keys to a set of typed values. Here are the three different ways in …
Free Online Books – Machine Learning with Python
This post lists down free online books for machine learning with Python. These books covers topiccs related to machine learning, deep learning, and NLP. This post will be updated from time to time as I discover more books. Here are the titles of these books: Python data science handbook Building machine learning systems with Python Deep learning with Python Natural language processing with Python Think Bayes Scikit-learn tutorial – statistical learning for scientific data processing Python Data Science Handbook Covers topics such as some of the following: Introduction to Numpy Data manipulation with Pandas Visualization with Matplotlib Machine learning topics (Linear regression, SVM, random forest, principal component analysis, K-means clustering, Gaussian …
Great Site for Matrix Multiplication Demo
Here is a great website for the matrix multiplication demo. If you are a beginner data scientist, you will love this. http://matrixmultiplication.xyz/ Here is how the website looks like. It has just one page. It actually shows how multiplication happens given the different dimensions of the matrix. Here are few other websites for understanding matrix multiplication concepts: https://www.mathsisfun.com/algebra/matrix-multiplying.html Khan Academy – Matrix multiplication
Different types of Machine Learning Problems
This post describes the most popular types of machine learning problems using multiple different images/pictures. The following represent various different types of machine learning problems: Supervised learning Unsupervised learning Reinforcement learning Transfer learning Imitation learning Meta-learning In this post, the image shows supervised, unsupervised, and reinforcement learning. You may want to check the explanation on this Youtube lecture video. Unsupervised Learning Problems In unsupervised learning problems, the learning algorithm learns about the structure of data from the given data set and generates fakes or insights. In the above diagram, you may see that what is given is the unlabeled dataset X. The unsupervised learning algorithm learns the structure of data …
Top 10+ Youtube AI / Machine Learning Courses
In this post, you get access to top Youtube free AI/machine learning courses. The courses are suitable for data scientists at all levels and cover the following areas of machine learning: Machine learning Deep learning Natural language processing (NLP) Reinforcement learning Here are the details of the free machine learning / deep learning Youtube courses. S.No Title Description Type 1 CS229: Machine Learning (Stanford) Machine learning lectures by Andrew NG; In case you are a beginner, these lectures are highly recommended Machine learning 2 Applied machine learning (Cornell Tech CS 5787) Covers all of the most important ML algorithms and how to apply them in practice. Includes 3 full lectures …
Scikit-learn vs Tensorflow – When to use What?
In this post, you will learn about when to use Scikit-learn vs Tensorflow. For data scientists/machine learning enthusiasts, it is very important to understand the difference such that they could use these libraries appropriately while working on different business use cases. When to use Scikit-learn? Scikit-learn is a great entry point for beginners data scientists. It provides an efficient implementation of many machine learning algorithms. In addition, it is very simple and easy to use. You can get started with Scikit-learn in a very easy manner by using Jupyter notebook. Scikit-learn can be used to solve different kinds of machine learning problems including some of the following: Classification (SVM, nearest neighbors, random …
Machine Learning – Training, Validation & Test Data Set
In this post, you will learn about the concepts of training, validation, and test data sets used for training machine learning models. The post is most suitable for data science beginners or those who would like to get clarity and a good understanding of training, validation, and test data sets concepts. The following topics will be covered: Data split – training, validation, and test data set Different model performance based on different data splits Data Splits – Training, Validation & Test Data Sets You can split data into the following different sets and each data split configuration will have machine learning models having different performance: Training data set: When you …
Why use Random Seed in Machine Learning?
In this post, you will learn about why and when do we use random seed values while training machine learning models. This is a question most likely asked by beginners data scientist/machine learning enthusiasts. We use random seed value while creating training and test data set. The goal is to make sure we get the same training and validation data set while we use different hyperparameters or machine learning algorithms in order to assess the performance of different models. This is where the random seed value comes into the picture. Different Python libraries such as scikit-learn etc have different ways of assigning random seeds. While training machine learning models using Scikit-learn, …
I found it very helpful. However the differences are not too understandable for me