Learning python to be a data scientist

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What you'll learn in this step:

What you'll learn in this step:

What is the data analysis process? What steps are involved, and how do they relate to the wider discipline of data analytics? In this video, we’ll give you a step-by-step guide to the process, detailing each stage and where it fits into a data analyst’s work! Like any scientific discipline, data analysis follows a rigorous step-by-step process. Each stage requires different skills and know-how. To get meaningful insights, though, it’s important to understand the process as a whole. An underlying framework is invaluable for producing results that stand up to scrutiny. In this video, we’ll explore and break down the main steps in the data analysis process. This will cover how to define your goal, collect data, and carry out an analysis. We’ll also use examples and highlight a few tools to make this process easier. This video will equip you with a much better understanding of the basics behind the data analysis process. For a deeper dive on the data analysis process, you can check out CareerFoundry’s detailed article here: https://bit.ly/TheDataAnalysisProcess Interested in getting started in data analytics? We also have a fantastic, free short course, to help give you a flavor of what it’s like to work in the field. Sign up here: https://bit.ly/GetStartedInDataAnalytics Video timestamps / chapters: (00:00) Intro (00:21) Step one: Defining the question (02:47) Step two: Collecting the data (05:22) Step three: Cleaning the data (07:11) Step four: Analyzing the data (08:21) Step five: Sharing your results (10:06) Outro We hope you enjoyed the video, thanks for watching! #DataAnalytics #Data #DataAnalysis Data Analytics: The Data Analysis Process (Step-By-Step) 2021 https://youtu.be/lgCNTuLBMK4

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This video covers the basics of plotting with the pandas library in Python, including how to make histograms, boxplots, scatter plots, bar plots and line plots. Subscribe: ► https://www.youtube.com/c/DataDaft?sub_confirmation=1 This is lesson 21 of a 30-part introduction to the Python programming language for data analysis and predictive modeling. Link to the code notebook below: Python for Data Analysis: Descriptive Statistics https://www.kaggle.com/hamelg/python-for-data-21-descriptive-statistics This guide does not assume any prior exposure to Python, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn Python. I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can copy and edit each lesson so that you can follow along and run code yourself. Introduction to Python Playlist: https://www.youtube.com/playlist?list=PLiC1doDIe9rCYWmH9wIEYEXXaJ4KAi3jc Link to the Python for Data Analysis written guide index page: https://www.kaggle.com/hamelg/python-for-data-analysis-index . ⭐ Kite is a free AI-powered coding assistant that integrates with popular editors and IDEs to give you smart code completions and docs while you’re typing. It is a cool application of machine learning that can also help you code faster! Check it out here: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=datadaft&utm_content=description-only

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This video covers the basics of working with probability distributions in Python, including the uniform, normal, binomial, geometric, exponential and Poisson distributions. It also includes a discussion of random number generation and setting the random seed. Subscribe: ► https://www.youtube.com/c/DataDaft?sub_confirmation=1 This is lesson 22 of a 30-part introduction to the Python programming language for data analysis and predictive modeling. Link to the code notebook below: Python for Data Analysis: Probability Distributions https://www.kaggle.com/hamelg/python-for-data-22-Probability-Distributions This guide does not assume any prior exposure to Python, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn Python. I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can copy and edit each lesson so that you can follow along and run code yourself. Introduction to Python Playlist: https://www.youtube.com/playlist?list=PLiC1doDIe9rCYWmH9wIEYEXXaJ4KAi3jc Link to the Python for Data Analysis written guide index page: https://www.kaggle.com/hamelg/python-for-data-analysis-index . ⭐ Kite is a free AI-powered coding assistant that integrates with popular editors and IDEs to give you smart code completions and docs while you’re typing. It is a cool application of machine learning that can also help you code faster! Check it out here: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=datadaft&utm_content=description-only

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What you'll learn in this step:

What you'll learn in this step:

Python Machine Learning Tutorial - Learn how to predict the kind of music people like. 👍 Subscribe for more Python tutorials like this: https://goo.gl/6PYaGF 👉 The CSV file used in this tutorial: https://bit.ly/3muqqta 🚀 Learn Python in one hour: https://youtu.be/kqtD5dpn9C8 🚀 Python (Full Course): https://www.youtube.com/watch?v=_uQrJ0TkZlc Want to learn more from me? Courses: https://codewithmosh.com Twitter: https://twitter.com/moshhamedani Facebook: https://www.facebook.com/programmingwithmosh/ Blog: http://programmingwithmosh.com #Python, #MachineLearning, #Jupyter TABLE OF CONTENT 0:00:00 Introduction 0:00:59 What is Machine Learning? 0:02:58 Machine Learning in Action 0:05:45 Libraries and Tools 0:10:40 Importing a Data Set 0:17:01 Jupyter Shortcuts 0:22:53 A Real Machine Learning Problem 0:26:09 Preparing the Data 0:29:15 Learning and Predicting 0:33:20 Calculating the Accuracy 0:39:41 Persisting Models 0:42:55 Visualizing a Decision Tree

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What you'll learn in this step:

🔥 Python Certification Training: https://www.edureka.co/data-science-python-certification-course This Edureka video on 'Predictive Analysis Using Python' covers the concept of making predictions based on data analysis and modeling using machine learning. Following are the topics discussed in this session: 00:00 - Introduction 00:53 - What is Predictive Analysis? 01:44 - Applications of Predictive Analysis 04:34 - Steps Involved in Predictive Analysis 08:54 - Predictive Analysis Using Python 🔹Python Tutorial Playlist: https://goo.gl/WsBpKe 🔹Blog Series: http://bit.ly/2sqmP4s ---------------------------------------------------------------------------------------------------------- 🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Edureka Community: https://bit.ly/EdurekaCommunity Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Telegram: https://t.me/edurekaupdates SlideShare: https://www.slideshare.net/EdurekaIN Meetup: https://www.meetup.com/edureka/ #Edureka #PythonEdureka #predictiveanalysis #machinelearning #pythonprojects #pythonprogramming #pythontutorial #PythonTraining ---------------------------------------------------------------------------------------------------------- How it Works? Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in the python programming language to enhance your learning experience. ---------------------------------------------------------------------------------------------------------- Why Learn Machine Learning using Python? Data Science is a set of techniques that enables computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning. After completing this Machine Learning Certification Training using Python, you should be able to: Gain insight into the 'Roles' played by a Machine Learning Engineer Automate data analysis using python Describe Machine Learning Work with real-time data Learn tools and techniques for predictive modeling Discuss Machine Learning algorithms and their implementation Validate Machine Learning algorithms Explain Time Series and it’s related concepts Gain expertise to handle business in the future, living the present Who should go for this Machine Learning Certification Training using Python? Edureka’s Python Machine Learning Certification Course is a good fit for the below professionals: Developers aspiring to be a ‘Machine Learning Engineer' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Machine Learning (ML) Techniques Information Architects who want to gain expertise in Predictive Analytics 'Python' professionals who want to design automatic predictive models ---------------------------------------------------------------------------------------------------------- For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free)

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In this video I'll show you how to quickly and easily access web apis and convert the resulting JSON data into a Python dictionary, pull the relevant information out, and print it. We'll be using TV Maze to get information about various TV shows. Links: TV Maze API Info: https://www.tvmaze.com/api JSON: https://www.json.org/json-en.html Code: import requests import json import pprint url = "http://api.tvmaze.com/singlesearch/shows" show = input("Please input a show name. ") params = {"q":show} response = requests.get(url, params) if response.status_code == 200: data = json.loads(response.text) # pprint.pprint(data) name = data['name'] premiered = data['premiered'] summary = data['summary'] print(f"{name} premiered on {premiered}.") print(summary) else: print(f"Error: {response.status_code}") NEED HELP? 🆘 Watch this first and then let me know in the comments below: https://www.youtube.com/watch?v=L6AwVuu6O3Y ❤️❤️ SHOW SOME LOVE AND SUPPORT THE CHANNEL ❤️❤️ Click Join and Become a Channel Member Today! Channel members can get preferential comment replies, early access to new content, members only live streams, and access to my private Discord. ❤️ https://www.youtube.com/channel/UC2vm-0XX5RkWCXWwtBZGOXg/join LINKS 🗄️ GITHUB: https://github.com/wynand1004 💬 Follow me on Twitter: https://twitter.com/tokyoedtech 📜 Subscribe to my Newsletter: http://eepurl.com/dKgM8k 📝 Check out my Blog: https://christianthompson.com ⬇️ Download Geany Editor: https://www.geany.org LEARN MORE PYTHON ➡️Space Invaders: https://www.youtube.com/watch?v=QvtlEj_T55o&list=PLlEgNdBJEO-lqvqL5nNNZC6KoRdSrhQwK ➡️Snake Game: https://www.youtube.com/watch?v=BP7KMlbvtOo&list=PLlEgNdBJEO-n8k9SR49AshB9j7b5Iw7hZ ➡️Pong: https://www.youtube.com/watch?v=LH8WgrUWG_I&list=PLlEgNdBJEO-kXk2PyBxhSmo84hsO3HAz2 ➡️Space War: https://www.youtube.com/watch?v=Ak1IDnP5IrI&list=PLlEgNdBJEO-muprNCDYiKLZ-Kc3-p8thS ➡️Intro to Python (for Java Coders): https://www.youtube.com/watch?v=hIulVFh4S-k&list=PLlEgNdBJEO-n4c4QMmUVknHxfjDlvbY1l ➡️Space Arena - The Ultimate Python Turtle Graphics Game Tutorial: https://www.youtube.com/watch?v=nUoJjHOlY24&list=PLlEgNdBJEO-kK78GXDVzytiZlJtCyiFyW LEARN MORE JAVA ➡️Basic Java for Beginners: https://www.youtube.com/watch?v=FxmQeC-3uuE&list=PLlEgNdBJEO-lCMWT4wd3VbZbv_swTd_eT ➡️Intro to AP Computer Science A: https://www.youtube.com/watch?v=1g99HckBk8c&list=PLlEgNdBJEO-kaJjwvtMrBBrm6-i4w1TQG #Python #Tutorial #API #JSON

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What you'll learn in this step:

What you'll learn in this step:

What you'll learn in this step:

What you'll learn in this step:

What you'll learn in this step:

🔥1000+ Free Courses With Free Certificates: https://www.mygreatlearning.com/academy?ambassador_code=GLYT_DES_Top_SEP22&utm_source=GLYT&utm_campaign=GLYT_DES_Top_SEP22 Looking for a career upgrade & a better salary? We can help, Choose from our no 1 ranked top programmes. 25k+ career transitions with 400 + top corporate companies. Exclusive for working professionals: https://glacad.me/3bf1TEK 🔥 Get the course material and session PDF Here: https://glacad.me/3v1S6Kr 🔥 Mining of Data is extremely important to find useful information, which can help to boost a company's revenue, increase market segment, or even cure a disease. The session starts with a basic overview and the terminologies involved in data mining and then gradually moves on to cover topics such as classification and prediction, decision tree induction, cluster analysis, and how to mine the Web. In this live session, we will also be comprehensively covering all the other concepts of data mining and also see how to implement them using python. ⚡ About Great Learning Academy: Visit Great Learning Academy to get access to 1000+ free courses with free certificate on Data Science, Data Analytics, Digital Marketing, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity, Software Development, and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. ⚡ About Great Learning: With more than 5.4 Million+ learners in 170+ countries, Great Learning, a part of the BYJU'S group, is a leading global edtech company for professional and higher education offering industry-relevant programs in the blended, classroom, and purely online modes across technology, data and business domains. These programs are developed in collaboration with the top institutions like Stanford Executive Education, MIT Professional Education, The University of Texas at Austin, NUS, IIT Madras, IIT Bombay & more. SOCIAL MEDIA LINKS: 🔹 For more interesting tutorials, don't forget to subscribe to our channel: https://glacad.me/YTsubscribe 🔹 For more updates on courses and tips follow us on: ✅ Telegram: https://t.me/GreatLearningAcademy ✅ Facebook: https://www.facebook.com/GreatLearningOfficial/ ✅ LinkedIn: https://www.linkedin.com/school/great-learning/mycompany/verification/ ✅ Follow our Blog: https://glacad.me/GL_Blog

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In this video, we're going to discuss how you can create an interactive Data Science Web Application using Python. Here we will use Streamlit, an open-source Python library, that makes it easy to build beautiful custom web apps for Machine Learning and Data Science. So, let's get started. Download the Dataset From - [https://bit.ly/3fjh4h7] Check Out the Related Article: Create Data Science App in Python Using Streamlit [https://www.geeksforgeeks.org/data-science-apps-using-streamlit/] WISH TO CONTRIBUTE VIDEOS ON GEEKSFORGEEKS? Please submit this Google Form - https://docs.google.com/forms/d/e/1FAIpQLScSVFlE-stz69M_l46xcwZlVRzDxT_91dlc-px5ytr7QHYmkQ/viewform Our courses: https://practice.geeksforgeeks.org/courses/ This video is contributed by Akshit Madan. Please Like, Comment, and Share the Video among your friends. #python #datascience #webapp #datascienceproject #pythonproject Install our Android App: https://play.google.com/store/apps/details?id=free.programming.programming&hl=en If you wish, translate into the local language and help us reach millions of other geeks: http://www.youtube.com/timedtext_cs_panel?c=UC0RhatS1pyxInC00YKjjBqQ&tab=2 Follow us on our Social Media Handles - Twitter- https://twitter.com/geeksforgeeks LinkedIn- https://www.linkedin.com/company/geeksforgeeks Facebook- https://www.facebook.com/geeksforgeeks.org Instagram- https://www.instagram.com/geeks_for_geeks/?hl=en Reddit- https://www.reddit.com/user/geeksforgeeks Telegram- https://t.me/s/geeksforgeeks_official Also, Subscribe if you haven't already! :)

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Target audience: Grades 10-12 Have you ever wondered how scientists transform data into a visual story? In this session, Josh will take you on a journey through the Python programming language from the ground up with real examples using data from the earth sciences. During this Tour de Python, you will learn about data visualization, earthquakes, plate tectonics, and even run your very own Python code! *Previous familiarity with Python or another programming language is helpful but not required. Details and more info: https://www.earth.columbia.edu/videos/view/part-1-of-2-data-storytelling-in-python-grades-10-12