Data Science with Python

DescriptionCombine Python with Machine Learning principles to discover hidden patterns in raw dataLeverage the power of the Python data science libraries and advanced machine learning techniques to analyse large unstructured datasets and predict the occurrence of a particular future event.Data Science with Python begins by introducing you to data science and teaches you to install the packages you need to create a data science coding environment. You will learn three major techniques in machine learning: unsupervised learning, supervised learning, and reinforcement learning. You will also explore basic classification and regression techniques, such as support vector machines, decision trees, and logistic regression.As you make your way through chapters, you will study the basic functions, data structures, and syntax of the Python language that are used to handle large datasets with ease. You will learn about NumPy and pandas libraries for matrix calculations and data manipulation, study how to use Matplotlib to create highly customizable visualizations, and apply the boosting algorithm XGBoost to make predictions. In the concluding chapters, you will explore convolutional neural networks (CNNs), deep learning algorithms used to predict what is in an image. You will also understand how to feed human sentences to a neural network, make the model process contextual information, and create human language processing systems to predict the outcome.By the end of this book, you will be able to understand and implement any new data science algorithm and have the confidence to experiment with tools or libraries other than those covered in the book.Key FeaturesExplore the depths of data science, from data collection through to visualizationLearn pandas, scikit-learn, and Matplotlib in detailStudy various data science algorithms using real-world datasetsWhat You Will LearnPre-process data to make it ready to use for machine learningCreate data visualizations with MatplotlibUse scikit-learn to perform dimension reduction using principal component analysis (PCA)Solve classification and regression problemsGet predictions using the XGBoost libraryProcess images and create machine learning models to decode themProcess human language for prediction and classificationUse TensorBoard to monitor training metrics in real timeFind the best hyperparameters for your model with AutoMLTarget AudienceData Science with Python is designed for data analysts, data scientists, database engineers, and business analysts who want to move towards using Python and machine learning techniques to analyze data and predict outcomes. Basic knowledge of Python and data analytics will prove beneficial to understand the various concepts explained through this book.Table of ContentsPrefaceIntroduction to Data Science and Data PreprocessingData VisualizationIntroduction to Machine Learning via Scikit-LearnDimensionality Reduction and Unsupervised LearningMastering Structured DataDecoding ImagesProcessing Human LanguageTips and Tricks of the TradeAuthors BiographyRohan Chopra is a data scientist at Absolutdata. He graduated from Vellore Institute of Technology with a bachelor’s degree in computer science. Rohan has 2 years of experience in designing, implementing, and optimizing end-to-end deep neural network systems. His research is centered around the use of deep learning to solve computer vision related problems and has hands-on experience working on self-driving cars.Mohamed Noordeen Alaudeen is a Lead Data Scientist at Logitech. He has ample of Experience in building and developing end-to-end Bigdata and Deep Neural Network Systems.He is a Seasonal Data Science and BigData trainer with Imarticus Learning and Great Learning to assist student. Apart from his teaching, He do contribute his work to opensource, He is active in github and stackoverflow. He owns a website and writes a blog from time to time. He is an active influencer in Linkedin helping the data science community when and where required.