Machine Learning

Product demand forecasting with Knime

Reading Time: 5 minutes In this blog, we are going to see, Importance of demand forecasting and how we can easily create these forecasting workflows with Knime. Market request forecasting is a basic procedure for any business, however maybe none more so than those in buyer packaged products. Stock, production, storage, delivering, showcasing – each aspect of CPG and retail organizations’ activities are influenced by accurate forecasting. Identifying shoppers’ Continue Reading

MachineX: Run ML model prediction faster with Hummingbird

Reading Time: 3 minutes In this blog, we will see how to make our machine learning model’s prediction faster with a recently open-sourced library Hummingbird. Nowadays, we can see a lot of frameworks for deploying or serving the machine learning model into production. As a result, It is a headache for a data scientist to choose between these frameworks, keeping in mind how their model either Sklearn or LightGBM Continue Reading

Knoldus-blog-AI-ML

Finding the nexus between intelligent technologies and business

Reading Time: 2 minutes Artificial Intelligence & Machine Learning has indeed taken over our lives at every step of the way. For example: Starting out for your holiday tomorrow? Your smartphone will automatically send you weather reports and suggest itineraries. Ever seen your email software suggest smart replies while you’re drafting emails or replying to one? That’s also AI at work.

Knime Analytics Platform: A dream for a data scientist

Reading Time: 3 minutes In this blog, we are going to see, what is the Knime analytics platform and its important features to create an analytics workflow in an easy way. Introduction to Knime Analytics Platform KNIME is a platform built for powerful analytics on a GUI based workflow. This means you do not have to know how to code to be able to work using KNIME and derive Continue Reading

MachineX: performance metrics for Model Evaluation

Reading Time: 6 minutes In this blog, we are going to see how to choose the right metrics for model evaluation in different kinds of applications. There are different metric categories based on the ML model/application, and we are going to cover the popular metrics used in the following problems: Classification Metrics (accuracy, precision, recall, F1-score, ROC, AUC) Regression Metrics (MSE, MAE) there are more metrics like Computer Vision Continue Reading

MachineX: Ultimate guide to NLP (Part 1)

Reading Time: 7 minutes In this blog, we are going to see some basic text operations with NLP, to solve different problems. This Blog is a part of a series Ultimate guide to NLP , which will focus on Basic text pre-processing techniques. Some of the major areas that we will be covering in this series of Blogs include the following: Text Pre-Processing Understanding of Text & Feature Engineering Continue Reading

covid 19 business impact

Leveraging AI/ML in Various Industries To Combat the Business Impact of COVID-19

Reading Time: 6 minutes Within a short span of a month, the world has transformed as the coronavirus pandemic took control of countries, economies, and people’s lives. Humanity watched in disbelief as this unprecedented phenomenon took shape and within weeks, the world has been shut down and the mantra, ‘Stay Home’  has become the new normal. With close to 2.4 million cases and 170,000 deaths worldwide (as of 21st Continue Reading

MachineX: Boosting performance with XGBoost

Reading Time: 5 minutes In this blog, we are going to see how XGBoost works and some of the important features of XGBoost with the help of an example. So, many of us heard about tree models and boosting techniques. Let’s put these concepts together and talk about XGBoost, the most powerful machine learning Algorithm out there. XGboost called for eXtreme Gradient Boosted trees. The name XGBoost, though, actually Continue Reading

TensorFlow Quantum: beauty and the beast

Reading Time: 4 minutes So, we are finally here, after a long wait, we are going to be in an era of quantum computing. TFQ, the beauty of TensorFlow and beast nature of quantum computing. Quantum computing is becoming a technology to observe more closely in 2020. We have seen some recent announcements from Honeywell, Google and others, it’s worth looking forward to new pieces of hardware coming this year. Now, Google has Continue Reading

MachineX: Sentiment analysis with NLTK and Machine Learning

Reading Time: 9 minutes In this blog, we are going to see how we can NLP library NLTK for sentiment analysis. Sentiment Analysis is a common NLP task nowadays. Every data scientist or a person working on data science needs to perform. Introduction to NLP Natural Language processing Natural Language Processing (NLP) is a subfield of artificial intelligence that helps computers understand human language. NLP enables machines to derive Continue Reading

MachineX: Anticipate Customer behavior for Retailing

Reading Time: 4 minutes In this blog, we are going to see the power of Customer behavior Anticipation and how it can derive the success of the retail sector. Nowadays, Machine learning is playing an important in the success of different sectors. we can talk about Healthcare, Finance, Manufacturing, Agriculture, now even in Education. Retail is one of the sectors, which is getting huge benefits from machine learning and Continue Reading

MachineX: Demystifying Market Basket analysis

Reading Time: 7 minutes In this blog, we are going to see how we can Anticipate customer behavior with Market Basket analysis By using Association rules. Introduction to Market Basket analysis Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in transactions. To put it another way, it Continue Reading

MachineX: The Power of Recommendation Engines

Reading Time: 4 minutes In this blog, we are going to talk about, what actually Recommendation Engines is and different types of same. You can see the full webinar, related to this blog here : Recommender Engines or Systems is one of the most mainstream utilization of data science today. They are utilized to predict the “rating” or “preference” that a user would provide for a thing. Pretty much Continue Reading