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This book charts the experiences, pitfalls and knowledge behind leading scientific ideas to successful startups. Written by one of Switzerland's top serial entrepreneurs, this book is a must-read for scientists and academicians who want to see their idea turn into a product and change the market. It is also pertinent for finance and business professionals who aspire to become technology entrepreneurs. Starting with personal qualities of an entrepreneur, Anil Sethi discusses successful ideas, technology evaluation, team formation, patents and investor expectations. To guide the entrepreneur, this book also analyzes deal closing, equity conversion and ideal exit strategies to follow. Ultimately Anil Sethi reveals the 'inside track' which helps understand what drives entrepreneurs and what they wouldn't admit.
WALL STREET JOURNAL BESTSELLER Every business owner dreams of success, but the majority of businesses are doomed to fail. This book offers a journey through the pitfalls that cause 90% of companies to crash—and the crucial remedies entrepreneurs can use to avoid (or fix) them. Kim Hvidkjær was 29 years old when he became a millionaire. Two years later, after a cluster of disasters, he found himself basically broke. Now, having rebuilt his fortune as the founder of several successful enterprises and studied thousands of failed startups, Hvidkjær has become an expert in failure: what it means, what it looks like, and the strategies that business owners can use to prevent it. In How to F*ck Up Your Startup, he takes us on an entertaining and enlightening journey through the complex patterns of failure in the life cycle of a business, covering: Attitude mistakes Business model missteps Market research snafus Funding and financial blunders Product development errors Organization oversights Sales slip-ups Growing pains Most important, he tackles what to do when your business has gone wrong. Hvidkjær fleshes out a tangible, usable blueprint for entrepreneurs looking to learn (the easy way) from the mistakes of businesses gone before. Chock-full of easy-to-follow business lessons that will keep you from f*cking up your startup, this down-to-earth guide offers crucial, actionable advice for seasoned business owners and startup founders alike. A masterclass in failure, How to F*ck Up Your Startup is required reading for reaching success.
For the littlest scientists, the whole wide world can be a laboratory for learning. Nurture their natural curiosity with A Head Start on Science, a treasury of 89 hands-on science activities specifically for children ages 3 to 6. The activities are grouped into seven stimulating topic areas: the five senses, weather, physical science, critters, water and water mixture, seeds, and nature walks.
The field of data science, big data, machine learning, and artificial intelligence is exciting and complex at the same time. Data science is also rapidly growing with new tools, technologies, algorithms, datasets, and use cases. For a beginner in this field, the learning curve can be fairly daunting. This is where this book helps. The data science solutions book provides a repeatable, robust, and reliable framework to apply the right-fit workflows, strategies, tools, APIs, and domain for your data science projects. This book takes a solutions focused approach to data science. Each chapter meets an end-to-end objective of solving for data science workflow or technology requirements. At the end of each chapter you either complete a data science tools pipeline or write a fully functional coding project meeting your data science workflow requirements. SEVEN STAGES OF DATA SCIENCE SOLUTIONS WORKFLOW Every chapter in this book will go through one or more of these seven stages of data science solutions workflow. STAGE 1: Question. Problem. Solution. Before starting a data science project we must ask relevant questions specific to our project domain and datasets. We may answer or solve these during the course of our project. Think of these questions-solutions as the key requirements for our data science project. Here are some templates that can be used to frame questions for our data science projects. Can we classify an entity based on given features if our data science model is trained on certain number of samples with similar features related to specific classes?Do the samples, in a given dataset, cluster in specific classes based on similar or correlated features?Can our machine learning model recognise and classify new inputs based on prior training on a sample of similar inputs?STAGE 2: Acquire. Search. Create. Catalog.This stage involves data acquisition strategies including searching for datasets on popular data sources or internally within your organisation. We may also create a dataset based on external or internal data sources. The acquire stage may feedback to the question stage, refining our problem and solution definition based on the constraints and characteristics of the acquired datasets. STAGE 3: Wrangle. Prepare. Cleanse.The data wrangle phase prepares and cleanses our datasets for our project goals. This workflow stage starts by importing a dataset, exploring the dataset for its features and available samples, preparing the dataset using appropriate data types and data structures, and optionally cleansing the data set for creating model training and solution testing samples. The wrangle stage may circle back to the acquire stage to identify complementary datasets to combine and complete the existing dataset. STAGE 4: Analyse. Patterns. Explore.The analyse phase explores the given datasets to determine patterns, correlations, classification, and nature of the dataset. This helps determine choice of model algorithms and strategies that may work best on the dataset. The analyse stage may also visualize the dataset to determine such patterns. STAGE 5: Model. Predict. Solve.The model stage uses prediction and solution algorithms to train on a given dataset and apply this training to solve for a given problem. STAGE 6: Visualize. Report. Present.The visualization stage can help data wrangling, analysis, and modeling stages. Data can be visualized using charts and plots suiting the characteristics of the dataset and the desired results.Visualization stage may also provide the inputs for the supply stage.STAGE 7: Supply. Products. Services.Once we are ready to monetize our data science solution or derive further return on investment from our projects, we need to think about distribution and data supply chain. This stage circles back to the acquisition stage. In fact we are acquiring data from someone else's data supply chain.
Most startups fail. But many of those failures are preventable. The Lean Startup is a new approach being adopted across the globe, changing the way companies are built and new products are launched. Eric Ries defines a startup as an organization dedicated to creating something new under conditions of extreme uncertainty. This is just as true for one person in a garage or a group of seasoned professionals in a Fortune 500 boardroom. What they have in common is a mission to penetrate that fog of uncertainty to discover a successful path to a sustainable business. The Lean Startup approach fosters companies that are both more capital efficient and that leverage human creativity more effectively. Inspired by lessons from lean manufacturing, it relies on “validated learning,” rapid scientific experimentation, as well as a number of counter-intuitive practices that shorten product development cycles, measure actual progress without resorting to vanity metrics, and learn what customers really want. It enables a company to shift directions with agility, altering plans inch by inch, minute by minute. Rather than wasting time creating elaborate business plans, The Lean Startup offers entrepreneurs—in companies of all sizes—a way to test their vision continuously, to adapt and adjust before it’s too late. Ries provides a scientific approach to creating and managing successful startups in a age when companies need to innovate more than ever.
Biotechnology Entrepreneurship: From Science to Solutions fills a critical gap in the biotechnology industry. For all the resources on how to start companies and on how to manage established companies in other sectors, there is a dearth of material on unique and critical issues in starting biotechnology companies, as well as managing the transition from start-up to established company. It is to this gap that Biotechnology Entrepreneurship is directed. By combining the voices of a diverse set of industry insiders with extensive experience in biotechnology, Biotechnology Entrepreneurship prepares nascent founders, managers, investors, and other biotechnology company stakeholders to position themselves and their companies for commercial success.
For readers of Michio Kaku and Stephen Hawking, the book readers have acclaimed as "A mega-comprehensive outlook at intelligence as convincing as it is surprising" and "A truly breathtaking forecast on the future of intelligence." With the ongoing advancement of AI and other technologies, our world is becoming increasingly intelligent. From chatbots to innovations in brain-computer interfaces to the possibility of superintelligences leading to the Singularity later this century, our reality is being transformed before our eyes. This is commonly seen as the natural result of progress, but what if there’s more to it than that? What if intelligence is an inevitability, an underlying property of the universe? In Future Minds, Richard Yonck challenges our assumptions about intelligence—what it is, how it came to exist, its place in the development of life on Earth and possibly throughout the cosmos. Taking a Big History perspective—over the 14 billion years from the Big Bang to the present and beyond—he draws on recent developments in physics and complexity theory to explore the questions: Why do pockets of increased complexity develop, giving rise to life, intelligence, and civilization? How will it grow and change throughout this century, transforming both technology and humanity? As we expand outward from our planet, will we discover other forms of intelligence, or will we conclude we are destined to go it alone? Any way we look at it, the nature of intelligence in the universe is becoming a central concern for humanity. Ours. Theirs. And everything in between.
The bestselling classic that launched 10,000 startups and new corporate ventures - The Four Steps to the Epiphany is one of the most influential and practical business books of all time. The Four Steps to the Epiphany launched the Lean Startup approach to new ventures. It was the first book to offer that startups are not smaller versions of large companies and that new ventures are different than existing ones. Startups search for business models while existing companies execute them. The book offers the practical and proven four-step Customer Development process for search and offers insight into what makes some startups successful and leaves others selling off their furniture. Rather than blindly execute a plan, The Four Steps helps uncover flaws in product and business plans and correct them before they become costly. Rapid iteration, customer feedback, testing your assumptions are all explained in this book. Packed with concrete examples of what to do, how to do it and when to do it, the book will leave you with new skills to organize sales, marketing and your business for success. If your organization is starting a new venture, and you're thinking how to successfully organize sales, marketing and business development you need The Four Steps to the Epiphany. Essential reading for anyone starting something new. The Four Steps to the Epiphany was originally published by K&S Ranch Publishing Inc. and is now available from Wiley. The cover, design, and content are the same as the prior release and should not be considered a new or updated product.
What the world can learn from Israel's meteoric economic success. Start-Up Nation addresses the trillion dollar question: How is it that Israel -- a country of 7.1 million, only 60 years old, surrounded by enemies, in a constant state of war since its founding, with no natural resources-- produces more start-up companies than large, peaceful, and stable nations like Japan, China, India, Korea, Canada and the UK? With the savvy of foreign policy insiders, Senor and Singer examine the lessons of the country's adversity-driven culture, which flattens hierarchy and elevates informality-- all backed up by government policies focused on innovation. In a world where economies as diverse as Ireland, Singapore and Dubai have tried to re-create the "Israel effect", there are entrepreneurial lessons well worth noting. As America reboots its own economy and can-do spirit, there's never been a better time to look at this remarkable and resilient nation for some impressive, surprising clues.