学习构建和部署数据科学、机器学习、DL项目(Python、Flask、Django、AWS、Azure、GCP、Heruko Cloud)
Ultimate Data Science Bootcamp: Build 50 Real Time Projects

你会学到什么
了解机器学习生命周期的完整产品工作流程。
创建用于预测连续值的回归机器学习算法。
数据科学和机器学习项目组合,提供所有代码和笔记本,可申请行业工作
了解真实数据集的最佳实践。
创建有监督的机器学习算法来预测类。
学习使用熊猫进行数据分析。
知道为每种类型的问题选择哪种机器学习模型
通过构建50个项目掌握数据科学
创建有监督的机器学习算法来预测类。

流派:电子学习| MP4 |视频:h264,1280×720 |音频:AAC,48.0 KHz
语言:英语+中英文字幕(根据原英文字幕机译更准确)|大小解压后:23.1 GB 含课程文件|时长:46小时



描述
机器学习是一项现代创新,它不仅帮助人类改进了许多工业和专业流程,还改善了日常生活。但是什么是机器学习呢?它是人工智能的一个子集,侧重于使用统计技术来构建智能计算机系统,以便从它可用的数据库中学习。目前,机器学习已经应用于多个领域和行业。例如医学诊断、图像处理、预测、分类、学习关联、回归等。

分类是将每个单独的替角安排在多个班级的过程。分类有助于分析对象的测量值,以确定该对象所属的类别。为了建立有效的关系,分析师使用数据。例如,在银行决定发放贷款之前,它会评估客户的贷款支付能力。通过考虑客户的收入、储蓄和金融历史等因素,我们可以做到这一点。这些信息来自过去的贷款数据。

机器学习也可以用于预测系统。考虑到贷款的例子,为了计算故障的概率,系统将需要对可用数据进行分组分类。它是由分析师规定的一套规则定义的。一旦分类完成,我们就可以计算出故障的概率。这些计算可以为各种目的跨所有扇区进行计算。做预测是最好的机器学习应用之一。

信息提取是机器学习的最佳应用之一。它是从非结构化数据中提取结构化信息的过程。例如,网页、文章、博客、商业报告和电子邮件。关系数据库维护信息提取产生的输出。提取过程以一组文档为输入,输出结构化数据。

我们也可以在回归中实现机器学习。在回归中,我们可以利用机器学习的原理来优化参数。它也可以用来减少近似误差和计算最接近的可能结果。我们也可以使用机器学习进行函数优化。我们也可以选择改变输入,以获得最接近的可能结果。

注:课程共有46小时点播视频,课程内容共有50个项目。



课程目录:
1.课程简介
2.项目-1 Pan Card回火检测器应用程序-在Heroku上部署
4.项目-3图像水印应用-部署在Heroku上
5.项目-4交通标志分类
3.项目-2狗品种预测烧瓶应用
6.项目-5从图像中提取文本应用
7.项目-6植物病害预测简化应用程序
8.项目-7车辆检测和计数瓶应用
9.项目-8创建一个面部交换烧瓶应用程序
10.项目-9鸟类物种预测烧瓶应用
11.项目-10英特尔图像分类烧瓶应用
12.项目-使用IBM云服务的11语言翻译应用程序-在Heroku上部署
13.项目-12使用IBM Watson预测广告视图-部署在Heroku上
14.项目-13笔记本电脑价格预测-在Heroku上部署
15.项目-14 WhatsApp文本分析器-部署在Heroku上
16.项目-15课程推荐系统-在Heroku上部署
17.项目-16 IPL比赛获胜预测-在Heroku上部署
18.项目-17体脂评估应用程序-在微软Azure上部署
19.项目-18校园安置预测应用程序-在微软Azure上部署
20.项目-19汽车可接受性预测-在谷歌云上部署
21.项目-20图书类型分类应用程序-在亚马逊网络服务上部署
22.项目-21情感分析Django应用程序-部署在Heroku
23.项目-22损耗率Django应用程序
24.项目-23寻找传奇口袋妖怪姜戈应用程序-部署在英雄库
25.项目-24人脸检测简化应用程序
26.项目-25猫Vs狗分类烧瓶应用
27.项目-26客户收入预测应用程序-在Heroku上部署
28.项目-27语音预测应用的性别-部署在Heroku上
29.项目-28餐厅推荐系统
30.项目-29幸福排名姜戈应用-部署在Heroku
31.项目-30森林火灾预测Django应用程序-部署在Heroku
32.项目-31构建汽车价格预测应用程序-在Heroku上部署
33.项目-32构建事务计数姜戈应用程序-部署在赫罗库
34.项目-33构建蘑菇预测应用程序-在Heroku上部署
35.项目-34谷歌游戏应用等级预测,在Heroku上部署
36.项目-35建立银行客户预测姜戈应用程序-部署在赫罗库
37.项目-36建造艺术家雕塑成本预测Django应用程序-部署在Heroku
38.项目-37构建医疗成本预测姜戈应用程序-部署在赫罗库
39.项目-38钓鱼网页分类Django应用程序-部署在Heroku上
40.项目-39服装尺寸预测姜戈应用程序-部署在赫罗库
41.项目-40构建文本中的相似性姜戈应用程序-部署在Heroku上
42.项目-41使用评估模型(自动模型)预测心脏病发作风险
43.项目-42使用Pycaret(自动ML)检测信用卡欺诈
44.项目-43使用自动学习预测航班票价
45.使用Auto Keras预测项目-44汽油价格
46.基于H2O汽车制造有限公司的项目-45银行客户流失预测
47.使用端到端部署的TPOT的项目-46空气质量指数预测器(A
48.项目-47使用最大似然模型预测降雨&带部署的PyCaret(自动最大似然)
49.项目-48使用最大似然法和最大似然法(自动最大似然法)预测比萨饼价格
50.项目-49 IPL板球得分预测使用TPOT(自动毫升)
51.项目-50使用ML和H2O汽车ML预测自行车租赁数量

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 48.0 KHz
Language: English | Size: 22.9 GB | Duration: 46 hours
Learn To Build & Deploy Data Science, Machine Learning, DL Projects (Python, Flask, Django,AWS,Azure, GCP, Heruko Cloud)

What you’ll learn
Understand the full product workflow for the machine learning lifecycle.
Create regression machine learning algorithms for predicting continuous values.
A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
Learn best practices for real-world data sets.
Create supervised machine learning algorithms to predict classes.
Learn to use Pandas for Data Analysis.
Know which Machine Learning model to choose for each type of problem
Master data science by building 50 projects
Create supervised machine learning algorithms to predict classes.

Description
Machine learning is one modern innovation that has helped man enhance not only many industrial and professional processes but also advances everyday living. But what is machine learning? It is a subset of artificial intelligence, which focuses on using statistical techniques to build intelligent computer systems in order to learn from databases available to it. Currently, machine learning has been used in multiple fields and industries. For example, medical diagnosis, image processing, prediction, classification, learning association, regression, etc.

Classification is a process of placing each individual understudy in many classes. Classification helps to analyze the measurements of an object to identify the category to which that object belongs. To establish an efficient relation, analysts use data. For example, before a bank decides to distribute loans, it assesses the customers on their ability to pay loans. By considering the factors like customers’ earnings, savings, and financial history, we can do it. This information is taken from the past data on the loan.

Machine learning can also be used in prediction systems. Considering the loan example, to compute the probability of a fault, the system will need to classify the available data in groups. It is defined by a set of rules prescribed by the analysts. Once the classification is done, we can calculate the probability of the fault. These computations can compute across all the sectors for varied purposes. Making predictions is one of the best machine learning applications.

The extraction of information is one of the best applications of machine learning. It is the process of extracting structured information from unstructured data. For example, web pages, articles, blogs, business reports, and emails. The relational database maintains the output produced by the information extraction. The process of extraction takes a set of documents as input and outputs the structured data.

We can also implement machine learning in the regression as well. In regression, we can use the principle of machine learning to optimize the parameters. It can also be used to decrease the approximation error and calculate the closest possible outcome. We can also use machine learning for function optimization. We can also choose to alter the inputs in order to get the closest possible outcome.

Note : Course has 46 hours on-demand video not 1h 58m And Course content Has 50 Project .

1. Introduction To The Course
2. Project-1 Pan Card Tempering Detector App -Deploy On Heroku
4. Project-3 Image Watermarking App -Deploy On Heroku
5. Project-4 Traffic sign classification
3. Project-2 Dog breed prediction Flask App
6. Project-5 Text Extraction From Images Application
7. Project-6 Plant Disease Prediction Streamlit App
8. Project-7 Vehicle Detection And Counting Flask App
9. Project-8 Create A Face Swapping Flask App
10. Project-9 Bird Species Prediction Flask App
11. Project-10 Intel Image Classification Flask App
12. Project-11 Language Translator App Using IBM Cloud Service -Deploy On Heroku
13. Project-12 Predict Views On Advertisement Using IBM Watson -Deploy On Heroku
14. Project-13 Laptop Price Predictor -Deploy On Heroku
15. Project-14 WhatsApp Text Analyzer -Deploy On Heroku
16. Project-15 Course Recommendation System -Deploy On Heroku
17. Project-16 IPL Match Win Predictor -Deploy On Heroku
18. Project-17 Body Fat Estimator App -Deploy On Microsoft Azure
19. Project-18 Campus Placement Predictor App -Deploy On Microsoft Azure
20. Project-19 Car Acceptability Predictor -Deploy On Google Cloud
21. Project-20 Book Genre Classification App -Deploy On Amazon Web Services
22. Project-21 Sentiment Analysis Django App -Deploy On Heroku
23. Project-22 Attrition Rate Django Application
24. Project-23 Find Legendary Pokemon Django App -Deploy On Heroku
25. Project-24 Face Detection Streamlit App
26. Project-25 Cats Vs Dogs Classification Flask App
27. Project-26 Customer Revenue Prediction App -Deploy On Heroku
28. Project-27 Gender From Voice Prediction App -Deploy On Heroku
29. Project-28 Restaurant Recommendation System
30. Project-29 Happiness Ranking Django App -Deploy On Heroku
31. Project-30 Forest Fire Prediction Django App -Deploy On Heroku
32. Project-31 Build Car Prices Prediction App -Deploy On Heroku
33. Project-32 Build Affair Count Django App -Deploy On Heroku
34. Project-33 Build Shrooming Predictions App -Deploy On Heroku
35. Project-34 Google Play App Rating prediction With Deployment On Heroku
36. Project-35 Build Bank Customers Predictions Django App -Deploy On Heroku
37. Project-36 Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku
38. Project-37 Build Medical Cost Predictions Django App -Deploy On Heroku
39. Project-38 Phishing Webpages Classification Django App -Deploy On Heroku
40. Project-39 Clothing Fit-Size predictions Django App -Deploy On Heroku
41. Project-40 Build Similarity In-Text Django App -Deploy On Heroku
42. Project-41 Heart Attack Risk Prediction Using Eval ML (Auto ML)
43. Project-42 Credit Card Fraud Detection Using Pycaret (Auto ML)
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)
45. Project-44 Petrol Price Forecasting Using Auto Keras
46. Project-45 Bank Customer Churn Prediction Using H2O Auto ML
47. Project-46 Air Quality Index Predictor Using TPOT With End-To-End Deployment (A
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)
49. Project-48 Pizza Price Prediction Using ML And EVALML(Auto ML)
50. Project-49 IPL Cricket Score Prediction Using TPOT (Auto ML)
51. Project-50 Predicting Bike Rentals Count Using ML And H2O Auto ML

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