What is Codecademy? Codecademy is a platform which students can use to gain knowledge about different types of programming languages. The platform consists of a large number of courses The platform consists of courses related to 12 programming languages along with HTML and CSS. Students can choose either the paid or the free membership to join the platform. The cost of the paid version is $39.99 per month. Price Plans of Codecademy Codecademy comes with two plans one of them is free and users do not have to pay anything. The paid plan is $39.99 per month. Why Codecademy alternatives? ... Read More

Introduction Cross Validation (CV) is a way of training machine learning models in which multiple models are trained on a part of the data and then accessing their performance or testing them on a independent unseen set of data. In the Cross-validation technique, we generally split the original train data into different parts iteratively so that the algorithm trains and validates itself on each portion of the data none of them are left out in the process In this article let us have a deep good understanding of the Cross-Validation technique and its significance in improving Model accuracy. Cross Validation ... Read More

Introduction Normality is defined as the phenomenon of belonging to a normal or Gaussian distribution in statistical terms. The normality of a dataset is the test for a dataset or variable if it follows a normal distribution. Many tests can be performed to check the normality of a dataset among which the most popular ones are the Histogram method, the QQ plot, and the KS Test. Normality testing – Checking for Normality There are both statistical and graphical approaches to determining the normality of a dataset or a feature. Let us look through some of these methods. Graphical Methods Histogram ... Read More

Introduction OOB or Out of Bag error and OOB Score is a term related to Random Forests. Random Forest is an ensemble of decision trees that improves the prediction from that of a single decision tree.OOB error is used to measure the error in the prediction of tree-based models like random forests, decision trees, and other ML models using the bagging method. In an OOB sample, the number of wrong classifications is an OOB error. In this article let's explore OOB error/score. Before moving ahead let us a short overview of Random Forest and Decision Trees. Random Forest Algorithm Random ... Read More

Introduction Today Machine Learning plays a crucial role in predicting stock prices and the growth of popular organizations and investment banks. While working on many such problems we consider many relations and correlations between different kinds of factors. The Anne Hathaway Effect is one such peculiar correlation related to popular businessman and investor Warren Buffet, Anne Hathaway, and his company Berkshire Hathaway(BRK). In this article let us know more about the effects and observations around this phenomenon. The Anne Hathaway Effect The Hathaway effect news was first picked up by CNBC. According to this effect, whenever Anne ... Read More

Introduction In the latest digital age, the accumulation and analysis of statistics have become crucial for businesses across numerous industries. Big records refer to large amounts of established and unstructured records that may be harnessed to extract precious insights. Massive facts revolutionize how corporations function, from healthcare to finance, marketing to transportation. In this article, we can explore the transformative strength of huge statistics across distinct sectors and apprehend its effect on choice−making, innovation, and purchaser experience. Healthcare Big records are revolutionizing the healthcare enterprise, allowing better patient care and medical studies. Electronic health facts (EHRs) seize patient records, allowing ... Read More

Big Data Big data alludes to the enormous volume, variety, and velocity of data created from different sources, including web−based entertainment, sensors, and cell phones, and that's just the beginning. The expression "big" includes the sheer volume of data and addresses the data's intricacy and variety. Big data is portrayed by its three V's − Volume Big data includes a huge amount of data that outperforms the handling abilities of conventional data set systems. The scale goes from terabytes (~ all of your PC extra room) to exabytes (~ all of your extra room X a million) and then some. ... Read More

The use of linear regression is a useful technique for figuring out and examining the relationship between variables. Predictive modeling relies on it and uses it as the cornerstone for many machine learning techniques. Machine learning requires a lot of optimization. It is comparable to improving a model to provide it with the best performance. Gradient descent, a key technique in optimization, enters the picture at this point. Consider it as a trustworthy ally that will help us navigate the vast array of potential model parameters to find the optimal ones. Gradient descent allows us to iteratively change these ... Read More

In the field of data mining, training artificial neural networks (ANNs) is extremely important. ANNs are potent computer models that draw inspiration from the complex operations of the human brain. ANNs have revolutionized data science, machine learning, and artificial intelligence through their capacity to spot patterns, learn from data, and predict the future. Extraction of insightful information from sizable and complicated datasets is what data mining, a crucial aspect of these disciplines, entails. By training ANNs, data scientists and practitioners can make use of the network's ability to unearth obscure patterns, spot trends, and create prediction models that might radically ... Read More

In data mining, the process of rating the usefulness and importance of patterns found is known as pattern evaluation. It is essential for drawing insightful conclusions from enormous volumes of data. Data mining professionals can assess patterns to establish the applicability and validity of newly acquired knowledge, facilitating informed decision−making and generating practical results. Several metrics and criteria, including support, confidence, and lift, are used in this evaluation method to statistically evaluate the patterns' sturdiness and dependability. In this post, we will be looking at pattern evaluation methods in data mining. Let’s begin. Understanding Pattern Evaluation In the field of ... Read More