Bøger af Luca Massaron

Unleash the power of Python for your data analysis projects with For Dummies! Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization.

Get a step ahead of your competitors with insights from over 30 Kaggle Masters and Grandmasters. Discover tips, tricks, and best practices for competing effectively on Kaggle and becoming a better data scientist.Purchase of the print or Kindle book includes a free eBook in the PDF format.Key Features:Learn how Kaggle works and how to make the most of competitions from over 30 expert KagglersSharpen your modeling skills with ensembling, feature engineering, adversarial validation and AutoMLA concise collection of smart data handling techniques for modeling and parameter tuningBook Description:Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career.The first book of its kind, The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond. Two Kaggle Grandmasters walk you through modeling strategies you won't easily find elsewhere, and the knowledge they've accumulated along the way. As well as Kaggle-specific tips, you'll learn more general techniques for approaching tasks based on image, tabular, textual data, and reinforcement learning. You'll design better validation schemes and work more comfortably with different evaluation metrics.Whether you want to climb the ranks of Kaggle, build some more data science skills, or improve the accuracy of your existing models, this book is for you.Plus, join our Discord Community to learn along with more than 1,000 members and meet like-minded people!What You Will Learn:Get acquainted with Kaggle as a competition platformMake the most of Kaggle Notebooks, Datasets, and Discussion forumsCreate a portfolio of projects and ideas to get further in your careerDesign k-fold and probabilistic validation schemesGet to grips with common and never-before-seen evaluation metricsUnderstand binary and multi-class classification and object detectionApproach NLP and time series tasks more effectivelyHandle simulation and optimization competitions on KaggleWho this book is for:This book is suitable for anyone new to Kaggle, veteran users, and anyone in between. Data analysts/scientists who are trying to do better in Kaggle competitions and secure jobs with tech giants will find this book useful.A basic understanding of machine learning concepts will help you make the most of this book.

Discover how algorithms shape and impact our digital world All data, big or small, starts with algorithms. Algorithms are mathematical equations that determine what we see based on our likes, dislikes, queries, views, interests, relationships, and more online.

This book is designed to guide you through TensorFlow and how to use it effectively. Throughout the book, you will work through recipes and get hands-on experience to perform complex data computations, gain insights into your data, and more.

This book is your guide to master deep learning with TensorFlow, with the help of 10 real-world projects. You will train high-performance models in TensorFlow to generate captions for images automatically, predict stocks' performance, create intelligent chatbots, perform large-scale text classification, develop recommendation systems, and more.

Explore the great features of the all-new JIRA 7 to manage projects and effectively handle bugs and software issuesKey Features Updated for JIRA 7, this book covers all the new features introduced in JIRA 7 with a dedicated chapter on JIRA Service Desk-one of the biggest new add-ons to JIRA This book lays a strong foundation to work with agile projects in JIRA from both the administrator and end user's perspective Learn to solve challenging data science problems by building powerful machine learning models using PythonBook DescriptionMachine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us.In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you'll acquire a broad set of powerful skills in the area of feature selection and feature engineering.The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python.This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python Machine Learning Cookbook by Prateek Joshi Advanced Machine Learning with Python by John Hearty Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca MassaronWhat you will learn Use predictive modeling and apply it to real-world problems Understand how to perform market segmentation using unsupervised learning Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Increase predictive accuracy with deep learning and scalable data-handling techniques Work with modern state-of-the-art large-scale machine learning techniques Learn to use Python code to implement a range of machine learning algorithms and techniquesWho this book is forThis Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected.