What are some cool data science projects?
Table of Contents
- 1 What are some cool data science projects?
- 2 Which are the most used open source tools for data science?
- 3 Where can I practice Python coding for data science?
- 4 How do I practice Python for data science?
- 5 What is the best project to start with Python?
- 6 What is the best open source project to analyze neuroimaging data?
What are some cool data science projects?
List of 10 interesting data science projects ideas to boost your career growth in data science.
- Chatbots.
- Credit Card Fraud Detection.
- Fake News Detection.
- Forest Fire Prediction.
- Classifying Breast Cancer.
- Sentiment Analysis.
- ColorDetection.
- Driver Somnolence Detection.
Which are the most used open source tools for data science?
Open Source Tools In this module, you will learn about three popular tools used in data science: GitHub, Jupyter Notebooks, and RStudio IDE. You will become familiar with the features of each tool, and what makes these tools so popular among data scientists today.
What can you do with Python for Data Science?
Web Development – Developers, engineers, and data scientists use Python for web scraping or creating a mock-up an app. Automating Reports – Analysts or product managers who need to make the same Excel report every single week can use Python to help create reports and save time.
What are the important topics in Python for Data Science?
Pandas – data manipulation and analysis. Matplotlib – plotting and visualization. Scikit-learn – machine learning and data mining. StatsModels – statistical modeling, testing, and analysis.
Where can I practice Python coding for data science?
The free course by Analytics Vidhya on Python is one of the best places to start your journey. This course focuses on how to get started with Python for data science and by the end you should be comfortable with the basic concepts of the language.
How do I practice Python for data science?
Plus, there are some complimentary technical skills we recommend you learn along the way.
- Step 1: Learn Python Fundamentals.
- Step 2: Practice Mini Python Projects.
- Step 3: Learn Python Data Science Libraries.
- Step 4: Build a Data Science Portfolio as you Learn Python.
- Step 5: Apply Advanced Data Science Techniques.
What are the most notable data science projects built in Python?
Let’s take a look at the most notable data science projects built in Python. 1. Predict Employee Computer Access Needs 2. Music Recommendation Engine 3. Build an Image Classifier for Plant Species Identification 4. Human Activity Recognition Using Smartphone Data Set 5. Product Price Suggestion 6. Performing Time Series Modelling 7.
What is the best open source machine learning library for Python?
Scikit-learn is another python open-source project. This is a very famous machine learning library for Python. Often used with NumPy and SciPy, scikit-learn offers classification, regression, and clustering- it has support for SVM (Support Vector Machines), random forests, gradient boosting, k-means, and DBSCAN.
What is the best project to start with Python?
56 Groundbreaking Python Open-source Projects – Get started with Python 1 Flask. 2 Keras. 3 spaCy. 4 Sentry. 5 OpenCV. 6 Nilearn. 7 scikit-learn. 8 PyTorch. 9 Librosa. 10 Gensim.
What is the best open source project to analyze neuroimaging data?
Nilearn is a part of the NiPy ecosystem, which is a community devoted to using Python for analyzing neuroimaging data. Scikit-learn is another python open-source project.