Wydawca: K-i-s-publishing

Applied Machine Learning Explainability Techniques. Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more

Aditya Bhattacharya

Applied Machine Learning for Healthcare and Life Sciences Using AWS. Transformational AI implementations for biotech, clinical, and healthcare organizations

Ujjwal Ratan

Applied Network Security. Proven tactics to detect and defend against all kinds of network attack

Warun Levesque, Arthur Salmon, Michael McLafferty

Applied SOA Patterns on the Oracle Platform. Fuse together your pragmatic Oracle experience with abstract SOA patterns with this practical guide

Sergey Popov

Applied Supervised Learning with Python. Use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning

Benjamin Johnston, Ishita Mathur

Applied Supervised Learning with R. Use machine learning libraries of R to build models that solve business problems and predict future trends

Karthik Ramasubramanian, Jojo Moolayil

Applied Unsupervised Learning with Python. Discover hidden patterns and relationships in unstructured data with Python

Benjamin Johnston, Aaron Jones , Christopher Kruger

Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA

Alok Malik, Bradford Tuckfield