Tag Archives: Data Science

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), data science, advanced analytics have been widely used for decades across different industries such as finance, healthcare, etc., but their …

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What is Human Data Science?

what is human data science

There’s a lot of buzz around the term “human data science.” What is it, and why should you care? Human data science is a relatively new field that combines the study of humans with the techniques of data science. By understanding human behavior and using big data techniques, unique and actionable insights can be obtained that weren’t possible before. In this blog post, we’ll discuss what human data science is and give some examples of how it’s being used today. What is human data science? Human data science is the study of humans using data science techniques. It’s a relatively new field that is growing rapidly as we learn more …

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Pricing Optimization & Machine Learning Techniques

pricing optimization and machine learning use cases

Pricing is a critical component of price optimization. In this blog post, we will dive into pricing optimization techniques and machine learning use cases. Price optimization techniques are used to optimize pricing for products or services based on customer response. AI / Machine learning can be leveraged in pricing optimization by using predictive analytics to predict consumer demand patterns and identify optimal prices for a products or services at a given time in the future. What is pricing optimization? Price optimization is a process where businesses use price discrimination to maximize revenue from customers. It is the process of pricing goods and services to maximize profits by taking into account …

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Supervised & Unsupervised Learning Difference

Supervised vs Unsupervised Machine Learning Problems

Supervised and unsupervised learning are two different common types of machine learning tasks that are used to solve many different types of business problems. Supervised learning uses training data with labels to create supervised models, which can be used to predict outcomes for future datasets. Unsupervised learning is a type of machine learning task where the training data is not labeled or categorized in any way. For beginner data scientists, it is very important to get a good understanding of the difference between supervised and unsupervised learning. In this post, we will discuss how supervised and unsupervised algorithms work and what is difference between them. You may want to check …

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Why & When to use Eigenvalues & Eigenvectors?

Eigenvector and Eigenvalues explained with example

In this post, you will learn about why and when you need to use Eigenvalues and Eigenvectors? As a data scientist/machine learning Engineer, one must need to have a good understanding of concepts related to Eigenvalues and Eigenvectors as these concepts are used in one of the most popular dimensionality reduction techniques – Principal Component Analysis (PCA). In PCA, these concepts help in reducing the dimensionality of the data (curse of dimensionality) resulting in a simpler model which is computationally efficient and provides greater generalization accuracy.   In this post, the following topics will be covered: Background – Why need Eigenvalues & Eigenvectors? What are Eigenvalues & Eigenvectors? When to use Eigenvalues …

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Cash Forecasting Models & Treasury Management

cash forecasting models methods treasury management

As a business owner, you are constantly working to ensure that your company has the cash it needs to operate. Cash forecasting is one of the most important aspects of treasury management, and it’s something that you should be paying attention to. Cash forecasting is a great example of where machine learning can have a real impact. By using historical data, we can build models that predict future cash flow for a company. This enables treasury managers to make better decisions about how to allocate resources and manage risks. As data scientists or machine learning engineers, it is important to be able to understand and explain the business value of …

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85+ Free Online Books, Courses – Machine Learning & Data Science

Machine Learning Books

This post represents a comprehensive list of 85+ free books/ebooks and courses on machine learning,  deep learning, data science, optimization, etc which are available online for self-paced learning.  This would be very helpful for data scientists starting to learn or gain expertise in the field of machine learning / deep learning. Please feel free to comment/suggest if I missed mentioning one or more important books that you like and would like to share. Also, sorry for the typos. Following are the key areas under which books are categorized: Data science Pattern Recognition & Machine Learning Probability & Statistics Neural Networks & Deep Learning Optimization Data mining Mathematics Here is my post …

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Posted in Big Data, Books, Career Planning, Data Science, Deep Learning, Machine Learning, Online Courses. Tagged with , , , .

Tensor Explained with Python Numpy Examples

Tensors are a hot topic in the world of data science and machine learning. But what are tensors, and why are they so important? In this post, we will explain the concepts of Tensor using Python Numpy examples with the help of simple explanation. We will also discuss some of the ways that tensors can be used in data science and machine learning. When starting to learn deep learning, you must get a good understanding of the data structure namely tensor as it is used widely as the basic data structure in frameworks such as tensorflow, PyTorch, Keras etc. Stay tuned for more information on tensors! What are tensors, and why are …

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Cohen Kappa Score Python Example: Machine Learning

Cohen Kappa Score Confusion Matrix

Cohen’s Kappa Score is a statistic used to measure the performance of machine learning classification models. In this blog post, we will discuss what Cohen’s Kappa Score is and Python code example representing how to calculate Kappa score using Python. We will also provide a code example so that you can see how it works! What is Cohen’s Kappa Score or Coefficient? Cohen’s Kappa Score, also known as the Kappa Coefficient, is a statistical measure of inter-rater agreement for categorical data. Cohen’s Kappa Coefficient is named after statistician Jacob Cohen, who developed the metric in 1960.   It is generally used in situations where there are two raters, but it …

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Artificial Intelligence (AI) for Telemedicine: Use cases, Challenges

In this post, you will learn about different artificial intelligence (AI) use cases of Telemedicine / Telehealth including some of key implementation challenges pertaining to AI / machine learning. In case you are working in the field of data science / machine learning, you may want to go through some of the challenges, primarily AI related, which is thrown in Telemedicine domain due to upsurge in need of reliable Telemedicine services. What is Telemedicine? Telemedicine is the remote delivery of healthcare services, using digital communication technologies. It has the potential to improve access to healthcare, especially in remote or underserved communities. It can be used for a variety of purposes, including …

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Scatter plot Matplotlib Python Example

Scatter Plot representing Two Classes

If you’re a data scientist, data analyst or a Python programmer, data visualization is key part of your job. And what better way to visualize all that juicy data than with a scatter plot? Matplotlib is your trusty Python library for creating charts and graphs, and in this blog we’ll show you how to use it to create beautiful scatter plots using examples and with the help of Matplotlib library. So dig into your data set, get coding, and see what insights you can uncover!  What is a Scatter Plot? A scatter plot is a type of data visualization that is used to show the relationship between two variables. Scatter …

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Weight Decay in Machine Learning: Concepts

Weight decay machine learning neural networks

Weight decay is a popular technique in machine learning that helps to improve the accuracy of predictions. In this post, we’ll take a closer look at what weight decay is and how it works. We’ll also discuss some of the benefits of using weight decay and explore some possible applications. As data scientists, it is important to learn about concepts of weight decay as it helps in building machine learning models having higher generalization performance. Stay tuned! What is weight decay and how does it work? Weight decay is a regularization technique that is used to regularize the size of the weights of certain parameters in machine learning models. Weight …

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K-Fold Cross Validation – Python Example

K-Fold Cross Validation Concepts with Python and Sklearn Code Example

In this post, you will learn about K-fold Cross-Validation concepts with Python code examples. K-fold cross-validation is a data splitting technique that can be implemented with k > 1 folds. K-Fold Cross Validation is also known as k-cross, k-fold cross-validation, k-fold CV, and k-folds. The k-fold cross-validation technique can be implemented easily using Python with scikit learn (Sklearn) package which provides an easy way to calculate k-fold cross-validation models.  It is important to learn the concepts of cross-validation concepts in order to perform model tuning with the end goal to choose a model which has a high generalization performance. As a data scientist / machine learning Engineer, you must have a good …

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Model Complexity & Overfitting in Machine Learning

model complexity vs model overfitting vs model accuracy

In machine learning, model complexity and overfitting are related in a manner that the model overfitting is a problem that can occur when a model is too complex due to different reasons. This can cause the model to fit the noise in the data rather than the underlying pattern. As a result, the model will perform poorly when applied to new and unseen data. In this blog post, we will discuss what model complexity is and how you can avoid overfitting in your machine learning models by handling the model complexity. As data scientists, it is of utmost importance to understand the concepts related to model complexity and how it …

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Activation Functions in Neural Networks: Concepts

The activation functions are critical to understanding neural networks. It is important to use the 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 to choose 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 the future. What are activation …

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Softmax Regression Explained with Python Example

In this post, you will learn about the concepts of what is Softmax regression/function with Python code examples and why do we need them? As data scientist/machine learning enthusiasts, it is very important to understand the concepts of Softmax regression as it helps in understanding the algorithms such as neural networks, multinomial logistic regression, etc in a better manner. Note that the Softmax function is used in various multiclass classification machine learning algorithms such as multinomial logistic regression (thus, also called softmax regression), neural networks, etc. Before getting into the concepts of softmax regression, let’s understand what is softmax function. What’s Softmax function? Simply speaking, the Softmax function converts raw …

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