Why RAG Chatbots Struggle in Production
“Our RAG chatbot worked perfectly in the POC.But once we scaled to 50,000 documents… accuracy dropped to 60%.” If you’ve…
Tag: Machine Learning
What is Stacking of Models in Machine Learning?
The last Ensemble method we will discuss in this series is called stacking (short for stacked generalization). It is based…
Ensemble Learning: A Comprehensive Guide to AdaBoost and Gradient Boosting
Introduction: In the realm of machine learning, ensemble learning techniques such as AdaBoost and Gradient Boosting have revolutionized the way…
Introduction to Dimensionality Reduction
The text discusses the curse of dimensionality in machine learning, highlighting challenges in high-dimensional spaces. It suggests reducing features to improve training efficiency and visualization, while addressing potential information loss and risks of overfitting with increased dimensions. Dimensionality reduction techniques will be explored further.
Sending Data in Unstructured File Form
Unstructured data files consist of a series of bits. The file doesn’t separate the bits from each other in any…
Random Forests | Machine Learning from Scratch
As we have discussed, a Random Forest is an ensemble of Decision Trees, generally trained via the bagging method (or…
Accessing Data in Structured Flat-File Form
In many cases, the data you need to work with won’t appear within a library, such as the toy datasets…
Gini Impurity or Entropy? How to decide the root node in decision tree?
By default, the Gini impurity measure is used, but you can select the entropy impurity measure instead by setting the…
Decision Trees | Machine Learning from Scratch
Like SVMs, Decision Trees are versatile Machine Learning algorithms that can perform both classification and regression tasks, and even multioutput…
How can A linear model learn non-linear/discrete patterns?
Introduction During model development, one of the techniques that many don’t experiment with is feature discretization. The core idea is…
Support Vector Machines (SVM) Algorithms
A Support Vector Machine (SVM) is a very powerful and versatile Machine Learning model, capable of performing linear or nonlinear…
What is early stopping? | Machine Learning from Scratch
Machine learning models, particularly those trained iteratively using algorithms like Gradient Descent, face the risk of overfitting the training data.…
Information Gain in Machine Learning
Information Gain (IG) is critical in machine learning and decision tree algorithms, particularly in data classification and 𝐟𝐞𝐚𝐭𝐮𝐫𝐞 𝐬𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧. Information…
What is Lasso Regression? | Machine Learning from Scratch
Least Absolute Shrinkage and Selection Operator Regression (simply called Lasso Regression) is another regularized version of Linear Regression: just like…
Regularized Linear Models(Ridge Regression) | Machine Learning from Scratch
As we saw in previous posts, a good way to reduce overfitting is to regularize the model (i.e., to constrain…
Learning Curves | Machine Learning from Scratch
Till now, We have read about Gradient Descent,Min-Batch Gradient Descent,Stochastic Gradient Descent and other type of Gradient Descents and Polynomial…