This repository contains my solutions to tasks from one month "Let's grow more" Data Science internship.
Task 1
Iris Flowers Classification ML Project : This particular ML project is usually referred to as the “Hello World” of Machine Learning. 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.
Task 2
Stock Market Prediction And Forecasting Using Stacked LSTM Datasetlinks: https://raw.githubusercontent.com/mwitiderrick/stockprice/master/NSE-TATAGLOBAL.csv
Task 3
Music Recommendation:
Music recommender systems can suggest songs to users based on their listening patterns. Datasetlinks: https://www.kaggle.com/c/kkbox-music-recommendation-challenge/data
Task 4:
Image to Pencil Sketch with Python
Task 5:
Exploratory Data Analysis on Dataset - Terrorism
As a security/defense analyst, try to find out the hot zone of terrorism.
You can choose any of the tool of your choice
Dataset: https://bit.ly/2TK5Xn5
Task 6:
Prediction using Decision Tree Algorithm. Create the Decision Tree classifier and visualize it graphically.
Task 7:
Develop A Neural Network That Can Read Handwriting:
Begin your 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. Dataset: https://en.wikipedia.org/wiki/MNIST_database
Task 8:
Next Word Prediction:
Using Tensorflow and Keras library train a RNN, to predict the next word. Dataset Link: https://drive.google.com/file/d/1GeUzNVqiixXHnTl8oNiQ2W3CynX_lsu2/view
Task 9:
Handwritten equation solver using CNN :
Mathematical equation solver using character and symbol recognition using image processing and CNN. DatasetLink: https://www.kaggle.com/xainano/handwrittenmathsymbols
Task 10:
ML Facial recognition to detect mood and suggest songs accordingly
DatasetLink: https://www.kaggle.com/datasets/msambare/fer2013