CSE NoticeBard presents a best-curated list of Machine learning courses for beginners from legit industry experts. Check the course details below!
About Machine Learning
Machine learning aims to discover patterns in your data and then make predictions based on often complex findings to answer business questions, detect and analyze trends, and help solve problems.
Best Tools for Machine Learning
There are several widely utilized tools and libraries for machine learning. Here are some notable examples:
- Python: Many machine learning frameworks and libraries are built using Python.
- TensorFlow: It provides a comprehensive ecosystem of tools, libraries, and community resources for building and deploying machine learning models.
- PyTorch: PyTorch is another popular open-source machine learning framework. It is known for its dynamic computation graph and is mostly used for deep learning research and applications.
- Scikit-learn: It is a library for Python that offers a diverse collection of supervised and unsupervised learning algorithms. It also includes an array of tools for data preprocessing and model evaluation. It is used for machine learning tasks.
- Keras: Keras is a top-level neural network library compatible with TensorFlow or Theano. It provides an easy-to-use interface for building and training deep learning models.
- Jupyter Notebook: Jupyter Notebook is a free-to-use web application that enables users to generate and distribute documents that feature dynamic code, equations, graphics, and written explanations. It is commonly used for interactive machine-learning prototyping and experimentation.
- Pandas: Pandas is a powerful Python library for data manipulation and analysis. It provides data structures and functions to efficiently work with structured data, making it helpful in preprocessing and cleaning data before feeding it into machine learning models.
- NumPy: NumPy is an entire library for numerical computing in Python. Many other libraries, including TensorFlow and sci-kit-learn, rely on NumPy.
- Matplotlib: It is a plotting library in Python that provides various visualizations. It is often used to create charts, histograms, scatter plots, and other plots to analyze and visualize data in machine learning projects.
- XGBoost: XGBoost is an open-source library that offers a gradient-boosting framework for machine learning. This tool boasts unparalleled performance and efficiency, making it the go-to choice for building top-notch gradient-boosting models.
