Welcome to this project on Getting Started with Git. In this project, you will understand how to use Git, one of the most famous distributed version-control systems to track changes in files and source code in your projects during software development.
In this exercise, you will learn about creating git repository, commits, branches, and merge branches. Additionally, you will learn how to create and clone a GitHub repository and SSH keys to push the changes to the remote repository.
Skills you will develop:
Welcome to this project on Getting Started with Git. In this project, you will understand how to use Git, one of the most famous distributed version-control systems to track changes in files and source code in your projects during software development.
In this exercise, you will learn about creating git repository, commits, branches, and merge branches. Additionally, you will learn how to create and clone a GitHub repository and SSH keys to push the changes to the remote repository.
Skills you will develop:
Welcome to this project on the Numpy - Cat vs Non-cat Classifier with Logistic Regression using Numpy. In this project, you will use Python and Numpy to build a Logistic Regression Classifier from scratch, and apply it to predict the class of an input image - whether it is a cat or a non-cat.
Though we have a lot of ready-made APIs like scikit-learn and Keras to build Machine Learning and Deep Learning models, it is very essential for a Machine Learning enthusiast to clearly understand the hidden mechanism behind the working of ML models. Upon completing this project, you will understand …
A gentle introduction to Artificial Neural Networks. Know more about perceptrons, backpropagation, and build an image classifier with Keras.
Learn more about Analytics and Data Science, probability, normal distribution, variance, data cleaning, feature scaling, standardization from industry experts.
Welcome to this project on the Titanic Machine Learning Project with Support Vector Machine Classifier and Random Forests using scikit-learn. In this project, you will use Python and scikit-learn to build SVC and random forest, and apply them to predict the survival rate of Titanic passengers.
Data preprocessing is one of the most prominent steps to make an effective prediction model in Machine Learning, and it is often a best practice to use data preprocessing pipelines. In this exercise, you will also learn how to build your custom data transformers and chain all these data pre-processing steps using scikit-learn pipelines …
Learn more about Analytics and Data Science, probability, normal distribution, variance, data cleaning, feature scaling, standardization from industry experts.
Welcome to this project on Image Classification with Pre-trained InceptionV3 Network. This project aims to impart the knowledge of how to access the pre-trained models(here we get pre-trained Inception model) from Keras of TensorFlow 2, and appreciate its powerful classification capacity by making the model predict the class of an input image.
Understanding the pre-trained models is very important because this forms the basis of transfer learning. one of the most appreciated techniques to perform the classification of a different task thus reducing the training time, the number of iterations, and resource consumption. Learning about the pre-trained models and …
Welcome to this project on Getting Started with Matplotlib. In this project, you will understand how to use Matplotlib, one of the most famous visualizing libraries in Python.
Data visualization is one of the most prominent ways of analyzing the data. It presents visually appealing ways to detect the patterns, noise, outliers, and many other insights, which would assist the data scientists to understand, transform, and refine the data to build better comprehensive models. This project would help you build data visualization skills on top of your existing Python programming skills. You will understand how to use Matplotlib to depict …