Task 01: Iris Flower Classification ML Project
The iris flowers dataset contains numeric attributes, and it is perfect for beginners to learn about supervised ML algorithms, mainly how to load and handle data. Also, since this is a small dataset, it can easily fit in memory without requiring special transformations or scaling capabilities. In this project I have use SVC model and checked the accuracy of model using Iris flower classification.
Task 02: Stock Market Prediction And Forecasting Using Stacked LSTM
Stock values is very valuable but extremely hard to predict correctly for any human being on their own. This task seeks to solve the problem of Stock Prices Prediction by stacked Long-Short Term Memory (LSTM), to predict future stock values.
Task 03: Image to Pencil Sketch with Python
We need to read the image in RBG format and then convert it to a grayscale image. This will turn an image into a classic black and white photo. Then the next thing to do is invert the grayscale image also called negative image, this will be our inverted grayscale image. Inversion can be used to enhance details. Then we can finally create the pencil sketch by mixing the grayscale image with the inverted blurry image. This can be done by dividing the grayscale image by the inverted blurry image. Since images are just arrays, we can easily do this programmatically using the divide function from the cv2 library in Python.
Task 04: Exploratory Data Analysis on Dataset - Terrorism
Perform ‘Exploratory Data Analysis’ on dataset ‘Global Terrorism’. As a security/defense analyst, try to find out the hot zone of terrorism. What all security issues and insights you can derive by EDA?
Task 05: Prediction using Decision Tree Algorithm
Create the Decision Tree classifier and visualize it graphically. The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.
Task 06: Develop A Neural Network That Can Read Handwriting
Here, I had try to classify English Alphabets with the help of a powerful Convolutional Neural Network.
TASK 7 : Next Word Prediction
Neural network machine learning project with the MNIST Handwritten Digit Classification Challenge and using Tensorflow and CNN. It has a very user-friendly interface that’s ideal for beginners.
Project has to classify handwritten digits using a simple neural network which has only input and output layers. Also adding a hidden layer and see how the performance of the model improves.