Machine Learning

MachineX: Alphabets of PyTorch (Part 1)

Reading Time: 6 minutes Overview In this blog, you’ll get an introduction to deep learning using the PyTorch framework, we will see some basics of PyTorch. Introduction to PyTorch PyTorch is a Python machine learning package based on Torch, which is an open-source machine learning package based on the programming language Lua. Two main features: Tensor computation (like NumPy) with strong GPU acceleration Automatic differentiation for building and training Continue Reading

MachineX: k-Nearest Neighbors(KNN) for Regression

Reading Time: 5 minutes Introduction K Nearest Neighbor Regression (KNN) works in much the same way as KNN for classification. The difference lies in the characteristics of the dependent variable. With classification KNN the dependent variable is categorical. With regression KNN the dependent variable is continuous. Both involve the use neighboring examples to predict the class or value of other examples. In this blog we will understand the basics Continue Reading

MachineX: Genetic Algorithm

Reading Time: 2 minutes Genetic algorithm is based on the Charles Darwin famous principle of survival of the fittest, where the fittest of the individuals are given higher importance and are chosen for reproduction in order to produce children for the new generation. The process starts by selecting the fittest individuals from a population, who then produce offspring which inherit the characteristics of the parents. Since the parents already Continue Reading

MachineX: Evaluation Metrics for a Regression ML Model

Reading Time: 3 minutes In this blog post, we will quickly look at the various metrics to evaluate our regression models. But first, let us briefly discuss one of the best-known model evaluation approach we use which is Train-Test or also known as Train-Validation split. Train-Test Split: In this approach, we split the data into two parts known as Training set and Test set. The model is then trained Continue Reading

TensorFlow for deep learning Part 1

Reading Time: 3 minutes TensorFlow is a free and Open-Source Software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library and is also used for machine learning applications such as neural networks. It is used for both research and production at Google. TensorFlow was developed by the Google Brain team for internal Google use. Deep learning is a particular kind of Continue Reading

MachineX: What is K-Fold Cross Validation?

Reading Time: 3 minutes In this blog, we are going to explore and learn about K-Fold Cross Validation. K-Fold Cross Validation is a statistical method to evaluate a Machine Learning model’s performance. So, to understand what K-Fold Cross Validation is, we first need to understand what evaluating a model means, and why do we need to do that.

MachineX: Logistic Regression with KSAI

Reading Time: 2 minutes Logistic Regression, a predictive analysis, is mostly used with binary variables for classification and can be extended to use with multiple classes as results also. We have already studied the algorithm in deep with this blog. Today we will be using KSAI library to build our logistic regression model. Setup

MachineX: Association Rule Learning with KSAI

Reading Time: 2 minutes In many of my previous blogs, I have posted about Association Rule Learning, what it’s about and how it is performed. In this blog, we are going to use Association Rule Learning to actually see it in action, and for this purpose, we are going to use KSAI, a machine learning library purely written in Scala. So, let’s begin. Adding KSAI to your project You Continue Reading

MachineX: A tour to KSAI – Neural Networks

Reading Time: 4 minutes In this blog we would look into how we can use KSAI; A machine learning library purely written in Scala using most of its feature and functional aspects of programming, you can read more about the library at KSAI Wiki, alternatively you can even fork the project from here, KSAI has a rich set of algorithms that address some of the vital problems in classification, Continue Reading

MachineX: An Introduction to KSAI, a machine learning library

Reading Time: 3 minutes Take a closer look at Linkedin or any media platform for a couple of minutes, you’ll find that the hot topic in the technology section nowadays is Machine Learning and Artificial Intelligence. Why Machine learning and artificial intelligence? Well needless to say it is transforming the world like anything. People are doing good in business by predicting different aspects, doctors are doing good in medical Continue Reading

Code Combat II : The Code Battle For The Vanguard Continues…

Reading Time: 4 minutes “If you can dream it, you can do it. ”  -Walt Disney For some coding is a job. For some, it is an exercise. But for us folks here at Knoldus, it’s a Passion. So in order to bring a twist in the daily work schedule, Knoldus held an overnight Hackathon competition within the organization on 18th May 2018 which presented an opportunity for every Knolder(employees Continue Reading

KnolX: NAIVE BAYES CLASSIFIER

Reading Time: < 1 minute Hi all, Knoldus has organized a 30 min session on 27th April 2018 at 4:00 PM. The topic was NAIVE BAYES CLASSIFIER. Many people have joined and enjoyed the session. I am going to share the slides here. Please let me know if you have any question related to linked slides.

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