12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
A neural network is a model that attempts to solve a complex problem by linking different units called neurons. These networks are built on the principle of neural activity, which was developed according to the way the brain works. Neural networks are a type of artificial intelligence used to solve complex tasks. They are widely used in pattern recognition, image recognition, game development and robotics.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Deep learning is a form of machine learning that uses complex models to analyze very large amounts of data. It is similar in many ways to the learning that the human brain uses to learn new concepts or insights. It is based on a set of algorithms called neural networks. These networks have individual connections that function like synapses in the brain. These connections are then layered to increase the complexity of the patterns they process. Deep Learning is particularly useful for automating processes and developing decision-making systems based on complex data.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Machine learning algorithms are algorithms that learn autonomously by analyzing information from existing data. They enable computer systems to learn from experience and apply it to new data and situations, allowing them to solve problems without explicit instructions. Machine learning algorithms include artificial neural networks, decision trees, support vector machines, Bayes networks, regression methods, and clustering algorithms.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
1. Data ingestion and analysis: data ingestion is the process of collecting, processing, and analyzing data from various sources to gain useful insights.
2. Data visualization: this is the process of presenting data in visual formats such as charts, graphs, and maps to identify trends and gain insights.
3. Machine learning: machine learning is a branch of artificial intelligence that enables computers to learn from experience without being explicitly programmed.
4. Predictive analytics: predictive analytics is a process of using data to predict possible future events and make decisions based on them.
5. Deep learning: deep learning is a subfield of machine learning in which so-called neural networks are used to solve complex problems.