Say Hello to Artificial Intelligence
Say Hello to Artificial Intelligence
I have been through many people who ask me about How to become Machine learning experts and do we require a PhD degree to become machine learning engineers? So before answering these questions I would like to briefly explain who is the machine learning Expert/Engineer? Who is ML Expert/Engineer? A Machine learning engineer is the …
There are several Machine Learning tools and techniques but choosing the right tool is really an important tasks for the practitioner and researchers. In this blog you will learn about most popular and widely used Machine learning tools. 1.Tensorflow Tensor flow is an open-source framework, which provides a JavaScript library for Machine Learning as well …
Most Popular and widely used Machine Learning tools in 2021 Read More »
After reading this blog you will understand what actually Machine learning is, how it differs from AI and Deep learning, the applications of ML, the basic architecture of ML and several types of ML. Machine Learning Machine learning (ML) can be described as a study that comprises of several algorithms and models, used by the …
1. Supervised Learning Supervised Learning is a machine learing type in which model is trained using data which is already tagged with correct anwer(label). it can be further grouped into Classifacion and Regression . 2. Unsupervised Learning Unsupervised Learning is a machine learing type in which model is trained using data that is neither classified …
1.Pandas pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the …
1.Linear Regression Linear Regression tends to establish a relationship between a dependent variable(Y) and one or more independent variable(X) by finding the best fit of the straight line.The equation for the Linear model is Y = mX+c, where m is the slope and c is the intercep. In the diagram, the blue dots we see …