Tag Archives: Data Science

Data Analytics – Different Career Options / Opportunities

data analytics career options

Data analytics career paths span a wide range of career options, from data scientist to data engineer. Data scientists are often interested in what they can do with the data that is analyzed, while data engineers are more focused on the analysis itself. Whether you’re looking for a career as a data scientist, data analyst, ML engineer, or AI researcher, there’s something for everyone! In this blog post, we will different types of jobs and careers available to those interested in data analytics and data science. What are some of the career paths in data analytics? Here are different career paths for those interested in data analytics career: Data Scientists: …

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Posted in AI, Career Planning, Data analytics, data engineering, Data Science, Machine Learning. Tagged with , , , .

Using Theory of Change to Design Data-driven Solutions

theory of change for data-driven decision making

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 …

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Key techniques for Evaluating Machine Learning models

AUC-ROC curve

Machine learning is a powerful machine intelligence technique that can be used to develop predictive models for different types of data. It has become the backbone of many intelligent applications and evaluating machine learning model performance at a regular intervals is key to success of such applications. A machine learning model’s performance depends on several factors including the type of algorithm used, how well it was trained and more. In this blog post, we will discuss  essential techniques for evaluating machine-learning model performance in order to provide you with some best practices when working with machine-learning models. The following are different techniques that can be used for evaluating machine learning …

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Posted in Data Science, Machine Learning. Tagged with , .

Top 50 Interview Questions for Beginner Data Scientists

interview questions for machine learning

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 …

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13 Machine Learning Use Cases for Climate Change

Climate change is a serious issue facing the world. The climate changes which are already affecting our planet can be seen in rising sea levels, melting ice caps and glaciers, more severe storms and hurricanes, more droughts, and wildfires increased precipitation in some areas of the world while other regions experience less rainfall. It’s important that we do what we can to reduce climate change risks by reducing greenhouse gas emissions into the atmosphere as well as adapting to climate impacts. Artificial intelligence (AI), machine learning (ML)/ deep learning (DL), advanced analytics have been widely used for decades across different industries such as finance, healthcare, etc., but their use cases …

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Posted in Climate Change, Data Science, Machine Learning. Tagged with , .

How to Create & Detect Deepfakes Using Deep Learning

create and detect deepfake 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? …

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Posted in Data Science, Deep Learning, Machine Learning. Tagged with , , .

Different Activation Functions in Neural Networks

Data scientists know that activation functions are critical to understanding neural networks. It is important to use activation function in order to train the neural network. There are many activation functions available for data scientists to choose from, so it can be difficult choosing which activation function will work best for their needs. In this blog post, we look at different activation functions and provide examples of when they should be used in different types of neural networks. If you are starting on deep learning and wanted to know about different types of activation functions, you may want to bookmark this page for quicker access in future. Without further ado, …

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Posted in Deep Learning, Machine Learning. Tagged with , , .

Mean Squared Error vs Cross entropy loss function

In this post, you will be learning the difference between two common types of loss functions: Cross-Entropy Loss and Mean Squared Error (MSE) Loss. These are both used in machine learning for classification & regression tasks, respecitively, to measure how well a model performs on unseen dataset. Both these losses are ways of measuring how well the predictions are made by classification and regression algorithms, and they both provide different information about the performance of models. As a data scientist, it is very important for you to understand the difference between loss functions in a great manner. What is cross-entropy loss? Cross entropy loss is used in classification tasks where …

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Procurement: Key Advanced Analytics Use Cases

procurement analytics use cases

The procurement analytics applications are poised to grow exponentially in the next few years. With so much data available, it’s important to know how procurement analytics can help you make better business decisions. This blog will cover procurement analytics and key use cases of advanced analytics that will be useful for data scientists implementing different use cases using machine learning. It is aimed at procurement professionals and data scientists who would like to use procurement analytics for making better business decisions. With so much data available nowadays it’s important to know how procurement analytics can help you make the best decision possible based on cost, quality, Procurement analytics allows you …

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Posted in Data Science, Machine Learning, Procurement. Tagged with , , .

How do we build Deep Neural Network using Perceptron?

Single layer neural network

In this post, you will understand about how a deep neural network is built using a perceptron. This is a very important concept in relation to getting a good understanding of deep learning. You will also learn related Tensorflow / Keras code snippet. Here are the key concepts related to how deep neural network is built using one or more perceptrons: First and foremost, it is key to understand what is a Perceptron? A perceptron is the most fundamental unit which is used to build a neural network. A perceptron resembles a neuron in the human brain. In case of a neuron, multiple input signals are fed into a neuron …

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Posted in Data Science, Deep Learning, Machine Learning. Tagged with , .

Examples of Generative Adversarial Network (GAN)

In this post, you will learn examples of generative adversarial network (GAN). The idea is to put together some of the interesting examples from across the industry to get a perspective on what problems can be solved using GAN. As a data scientist or machine learning engineer, it would be imperative upon us to understand the GAN concepts in a great manner to apply the same to solve real-world problems. This is where GAN network examples will prove to be helpful. Here are some examples of GAN network usage. Text to image translation Image editing / manipulating Creating images (2-dimensional images) Recreating images of higher resolution Creating 3-dimensional object Text to …

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Posted in Data Science, Deep Learning, Machine Learning. Tagged with , , .

Perceptron Explained using Python Example

In this post, you will learn about the concepts of Perceptron with the help of Python example. It is very important for data scientists to understand the concepts related to Perceptron as a good understanding lays the foundation of learning advanced concepts of neural networks including deep neural networks (deep learning).  In this post, the following topics are covered: What is Perceptron? Perceptron Python code example What is Perceptron? Perceptron is a machine learning algorithm which mimics how a neuron in the brain works. It is also called as single layer neural network consisting of a single neuron. The output of this neural network is decided based on the outcome of just one activation …

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Posted in Data Science, Deep Learning, Machine Learning. Tagged with , , , .

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 …

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Posted in Career Planning, Data Science, Deep Learning, Machine Learning, Tutorials. Tagged with , , , , .

Online AI News from Top Global Universities – List

US universities ai news and events

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 …

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MOSAIKS for creating Climate Change Models

MOSAIKS models comparison with Resnet and pre-trained CNN 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 …

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Posted in AI, Climate Change, Data Science, Machine Learning. Tagged with , .

Machine Learning – Feature Selection vs Feature Extraction

Feature extraction vs feature selection

In this post, you will learn about the difference between feature extraction and feature selection concepts and techniques. Both feature selection and feature extraction are used for dimensionality reduction which is key to reducing model complexity and overfitting. The dimensionality reduction is one of the most important aspects of training machine learning models. As a data scientist, you must get a good understanding of dimensionality reduction techniques such as feature extraction and feature selection. In this post, the following topics will be covered: Feature selection concepts and techniques Feature extraction concepts and techniques When to use feature selection and feature extraction Feature Selection Concepts & Techniques Simply speaking, feature selection …

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Posted in Data Science, Machine Learning. Tagged with , .