New Releases by Tiffany Ford

Discover how you can supervise machine learning algorithms in Python and personalize predictive models with the help of real-world datasets Key Features Explore the fundamentals of supervised machine learning and its applications Learn how to label and process data correctly using Python libraries Gain a comprehensive overview of different machine learning algorithms used for building prediction models Book DescriptionWould you like to understand how and why machine learning techniques and data analytics are spearheading enterprises globally? From analyzing bioinformatics to predicting climate change, machine learning plays an increasingly pivotal role in our society. Although the real-world applications may seem complex, this book simplifies supervised learning for beginners with a step-by-step interactive approach. Working with real-time datasets, you’ll learn how supervised learning, when used with Python, can produce efficient predictive models. Starting with the fundamentals of supervised learning, you’ll quickly move to understand how to automate manual tasks and the process of assessing date using Jupyter and Python libraries like pandas. Next, you’ll use data exploration and visualization techniques to develop powerful supervised learning models, before understanding how to distinguish variables and represent their relationships using scatter plots, heatmaps, and box plots. After using regression and classification models on real-time datasets to predict future outcomes, you’ll grasp advanced ensemble techniques such as boosting and random forests. Finally, you’ll learn the importance of model evaluation in supervised learning and study metrics to evaluate regression and classification tasks. By the end of this book, you’ll have the skills you need to work on your real-life supervised learning Python projects.What you will learn Import NumPy and pandas libraries to assess the data in a Jupyter Notebook Discover patterns within a dataset using exploratory data analysis Using pandas to find the summary statistics of a dataset Improve the performance of a model with linear regression analysis Increase the predictive accuracy with decision trees such as k-nearest neighbor (KNN) models Plot precision-recall and ROC curves to evaluate model performance Who this book is for If you are a beginner or a data scientist who is just getting started and looking to learn how to implement machine learning algorithms to build predicting models, then this book is for you. To expedite the learning process, a solid understanding of Python programming is recommended as you’ll be editing the classes or functions instead of creating from scratch.

Cut through the noise and get real results with a step-by-step approach to data science Key Features Ideal for the data science beginner who is getting started for the first time A data science tutorial with step-by-step exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book DescriptionYou already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You''ll learn from real examples that lead to real results. Throughout The Data Science Workshop, you''ll take an engaging step-by-step approach to understanding data science. You won''t have to sit through any unnecessary theory. If you''re short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It''s your choice. Learning on your terms, you''ll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you''ll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You''ll even earn a secure credential that you can share and verify online upon completion. It''s a premium learning experience that''s included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You''ll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you''ll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.What you will learn Find out the key differences between supervised and unsupervised learning Manipulate and analyze data using scikit-learn and pandas libraries Learn about different algorithms such as regression, classification, and clustering Discover advanced techniques to improve model ensembling and accuracy Speed up the process of creating new features with automated feature tool Simplify machine learning using open source Python packages Who this book is for Our goal at Packt is to help you be successful, in whatever it is you choose to do. The Data Science Workshop is an ideal data science tutorial for the data science beginner who is just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.