• Machine Learning

Machine learning is a field of study where computers learn patterns from data to make predictions or decisions. It is a fundamental aspect of data science that helps automate and optimize tasks using algorithms.

• Deep Learning

Deep learning is a subset of machine learning that focuses on training artificial neural networks to process and analyze complex data, enabling them to make sophisticated predictions or classifications.

• Computer Vision

Computer vision is a branch of artificial intelligence that deals with enabling computers to interpret and understand visual information, allowing them to analyze and extract meaningful insights from images or videos.

• Data Visualization

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. It also provides an excellent way for employees or business owners to present data to non-technical audiences without confusion.

• NumPy

Numpy is a library for python, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

• Pandas

Pandas is a software library written for python for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.

• Feature Engineering (Extraction)

Feature engineering or feature extraction or feature discovery is the process of using domain knowledge to extract features from raw data.

• Data Collection

Data collection is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. It’s a research component in all study fields, including physical and social sciences, humanities, and business.