Speech recognition systems use various algorithms and techniques to interpret the acoustic patterns of speech and map them to corresponding text representations. This technology which converts spoken language into written…
To convert text to speech in Python, you can use the gTTS API, or pyttsx3 library, which is a Text-to-Speech (TTS) engine that works offline. There are number of APIs…
In simple words, simple linear regression is finding the best fit line for one input and one output variable and predict the output value for each given input data. Here…
These techniques allow you to identify relationships, dependencies, and interactions between variables in your dataset. We have already seen univariate analysis in previous article. Here we will explore more on…
Univariate analysis helps to understand the distribution, central tendency, dispersion, and other key characteristics of each variable in your dataset. It is nothing but analysis of a single column. Univariate…
Understanding data is a critical step in machine learning. Before developing and training a model, it's essential to gain insights from our data we're working with. In this article I…
We are going to Build an End-to-End Machine Learning Project. This demo project will help you how to think while working on End-to-End machine Learning Project. This will help you…
In machine learning world tensors are multi-dimensional arrays used to represent and manipulate data. They are a fundamental data structure in many machine learning frameworks, such as TensorFlow and PyTorch.…
Machine learning is a subset of artificial intelligence that tells us about the development of algorithms and statistical models which actually allow computers to learn and make predictions or make…
The train-test-split function in sklearn helps you split your data into two groups, one for training your model and another one for testing to see how well your model works.…
Akshay Tekam