Join Python4Delphi author Kiriakos Vlahos, and Embarcadero Developer Advocate Jim McKeeth for this 2 part webinar to learn how to leverage Python in your Delphi applications.
Update: Because there was so much interest we are making this is a two-part webinar: Combining the strengths of Delphi and Python.
- Using python libraries and objects in Delphi code
- Python based data analytics in Delphi applications
- Creating Python extension modules using Delphi
- Python GUI development using the VCL
What sort of Python libraries can you access from Delphi with Python4Delphi?
- TensorFlow – Machine Learning
- TensorFlow, developed by Google in collaboration with Brain Team, is used in almost every Google application for machine learning.
- Neural networks can be easily expressed as computational graphs using TensorFlow as a series of operations on Tensors.
- Numpy – Data Cleaning and Manipulation
- TensorFlow and other libraries use Numpy internally for performing multiple operations on Tensors. The array interface is the best and the most important feature of Numpy.
- Pandas – Data manipulation and analysis
- In particular, it offers data structures and operations for manipulating numerical tables and time series.
- The name is derived from the term “panel data”, an econometrics term for data sets that include observations over multiple time periods for the same individuals.
- Scikit-Learn – Machine learning and modeling
- It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means, and DBSCAN.
- Natural Language Toolkit (NLTK) – Text Processing
- A suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English
- Intended to support research and teaching in NLP or closely related areas, including empirical linguistics, cognitive science, artificial intelligence, information retrieval, and machine learning
- SciPy – Data Science
- Used in science, mathematics, and engineering
- Contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers, and other tasks common in science and engineering.
- Matplotlib & Seaborn for plotting, and statistical data visualization
- Pillow & MoviePy for image and video processing