课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
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Next steps - SQL教程
课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
Next steps
- You've now come to the end of your journey and it's time to celebrate. You've got reason to celebrate. Artificial intelligence is revolutionizing your world and you're no longer a spectator. You understood the theory and put it to practice by building your very own linear regression model to predict home prices. So what now? Here are some next steps you can take. First up, get some rest. You deserve it. This stuff is not a walk in the park. It's involved and demands your attention and focus. After catching your breath a bit, consider focusing on Python and getting a good grasp of this powerful programming language. As you saw, to build an artificial intelligence solution, Python plays a critical role. Next up, SQL. Now, even though it worked quietly behind the scenes in the initial steps of the project, SQL is the language of databases and it has its place in data preparation, data retrieval, and data…
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内容
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Dive Into machine learning with regression3 分钟 41 秒
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Understanding the essentials of linear regression4 分钟 47 秒
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Navigating the world of multiple regression3 分钟 59 秒
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Decoding the secrets of the regression line3 分钟 44 秒
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Perfecting your model: Evaluation and validation3 分钟 49 秒
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From Predicting to Understanding4 分钟 46 秒
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Breaking Down Data Relationships with Regression4 分钟 6 秒
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Crafting Elegance in Machine Learning Models2 分钟 55 秒
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Hitting the Right Note - The Bias-Variance Trade-off4 分钟 7 秒
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Fine-Tuning Your Models3 分钟 33 秒
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Remixing Data with Bootstrapping3 分钟 49 秒
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Regression Analysis: A Practical Application3 分钟 54 秒
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Model Diagnostics and Assumption Testing5 分钟 18 秒
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Unlocking the Secrets Behind Coefficients3 分钟 55 秒
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Polynomial Paths and Interactions3 分钟 33 秒
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Striking a Balance with Regularization Techniques3 分钟 34 秒
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Beyond the Basics - Advanced Model Evaluation Metrics3 分钟 58 秒
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Non-parametric Regression Methods4 分钟 24 秒
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Case Studies in Regression Analysis3 分钟 3 秒
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Importing necessary libraries and dataset overview3 分钟 18 秒
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Loading the data7 分钟 36 秒
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Checking the data info2 分钟 13 秒
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Summary statistics of the dataset5 分钟 49 秒
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Checking the distribution of the variables5 分钟 42 秒
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Applying log transformation and re-checking distribution3 分钟 6 秒
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Challenge: Preparation1 分钟 5 秒
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Solution: Preparation1 分钟 19 秒
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Bivariate analysis: Heat-map5 分钟 23 秒
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Visualizing relationships: Age of homes and distance to work3 分钟 52 秒
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Visualizing relationships: Highway access and property tax4 分钟 9 秒
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Checking correlation after removing outliers3 分钟 40 秒
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Visualizing relationships: Other pairs of variables5 分钟 8 秒
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Challenge: Visualization1 分钟 9 秒
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Solution: Visualization56 秒
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Creating the linear regression model and model summary: Part 19 分钟 33 秒
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Creating the linear regression model and model summary: Part 27 分钟 16 秒
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Creating the linear regression model and model summary: Part 35 分钟 33 秒
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Dropping insignificant variables and re-creating the model7 分钟 57 秒
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Checking assumptions for linear regression3 分钟 18 秒
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Assumption 1: Checking for mean residuals2 分钟 47 秒
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Assumption 2: Checking homoscedasticity3 分钟 13 秒
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Assumption 3: Checking linearity2 分钟 12 秒
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Assumption 4: Checking normality of error terms3 分钟 24 秒
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Q-Q plot for checking the normality of error terms3 分钟 14 秒
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Model performance comparison on train and test data6 分钟 7 秒
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Applying cross-validation and evaluation4 分钟 40 秒
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Challenge: Model building48 秒
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Solution: Model building1 分钟 16 秒
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