Unreasonable Claim of Reasoning Ability of LLM Reasoning is critical for problem solving, decision making and in general for human intelligence. There have been various claims of reasoning abilities of LLM. Typically these claims [...]
Time Series Data Exploration with Wavelet Transform Time series data provides time domain information and Fast Fourier Transform provides frequency domain information only. What if you wanted both, for example you may be interested [...]
Customization of LLM ChatBots with Retrieval Augmented Generation For many domain specific business application the pre trained LLM is not enough. Customization is necessary. Out of the box pre trained black box models, even [...]
Time Series Sequence Anomaly Detection with Markov Chain There are many algorithms for anomaly detection in time series including Deep Learning based solutions. The anomalies are of 2 types, point and sequence. Sequence anomaly [...]
Recently I started working on a Python package which is everything time series, with specific focus on EDA, forecasting, classification and anomaly detection. It will leverage other Python libraries wherever appropriate. My first realization [...]
AI - Past, Present, and Future AI has gone through many cycles of ups and downs. There has been stunning progress as well as a disappointing slump. Fueled by Machine Learning and specifically, [...]
Machinery Fault Detection with Vibration Data Anomaly Detection using Variational Auto Encoder Auto Encoder is a unsupervised Deep Learning model. Data is encoded to a lower dimensional latent space using an encoder network. [...]
Optimization involves finding a set of problem parameter values that corresponds to minimization of some cost value. There is a class optimization algorithms calledHeuristic Optimization for real world complex non linear optimization problems. Many of [...]
Portfolio balancing is a complex optimization problem. The problem can be stated as assignment of weights to different stocks in the portfolio so that a metric called Sharpe Ratio is maximized. In this post we will [...]
There are two main kinds of problems in Reinforcement Learning (RL), evaluation of a policy aka the prediction problem and finding the best policy aka the control problem. A policy dictates the action to be taken given [...]
