This Repository serves as the central place for all Beginner-Level Machine Learning Projects implemeneted using Python and Jupyter Notebooks. It contains all the Files and Datasets required to implement beginner-level Machine Learning Projects using Toy Datasets and serves as a good place for beginners to check out Machine Learning Projects and start implementing them.
Using the Fuel Consumption Dataset which consists of model-specific fuel consumption ratings and estimated carbon dioxide emissions for new light-duty vehicles for retail sale in Canada. Using Simple Linear Regression you have to predict the Emission.
Using the Boston Housing Dataset you have to predict the value of prices of the house using the given features in the Dataset using Multiple Linear Regression.
Using the Breast Cancer Dataset you have to predict if the tumour is benign or malignant, using Logistic Regression.
Using the PIMA Indians Diabetes Dataset you have to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset, using Naive Bayes.
Using the MNIST Dataset you have to develop an Artificial Neural Network to predict Hand-Written Digits.
Utilize Natural Language Processing, predict the Gender of a Person given their name. Use Natural Language Toolkit and the Indian Names Dataset to predict the Gender of a Person.
Use CIFAR-10 Dataset to predict the class of the Object.
Contributions are welcome. Refer to the Issues and Contribution Guidelines for making the Projects.