標(biāo)題: Titlebook: Building an Effective Data Science Practice; A Framework to Boots Vineet Raina,Srinath Krishnamurthy Book 2022 Vineet Raina and Srinath Kri [打印本頁] 作者: 哄笑 時間: 2025-3-21 17:18
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作者: pus840 時間: 2025-3-21 23:56 作者: 即席 時間: 2025-3-22 04:01 作者: glans-penis 時間: 2025-3-22 08:34 作者: 配偶 時間: 2025-3-22 11:09
Anomaly Detectiongs that are rarely seen; an unheard-of combination of symptoms/test readings, or a rare pattern in a medical image such as a CT scan; and network traffic in an IT system that is unusual, these are a few cases that tend to raise attention. Detecting any abnormal occurrences in the data is referred to作者: dialect 時間: 2025-3-22 16:40 作者: 哥哥噴涌而出 時間: 2025-3-22 19:26
Sequential Decision-Makingwith a view to gaining a desired outcome in the longer run. The “desired outcome” can take various forms – maximizing profits/rewards (e.g., in an investment strategy), maximizing the chances to realize a targeted goal (e.g., winning in a competition such as chess), or saving patients with life-thre作者: 時代 時間: 2025-3-22 23:44 作者: DECRY 時間: 2025-3-23 04:17
Machine Learning dedicated to the ML algorithms/techniques you can use to build models and libraries that implement these algorithms. Awareness of different ML algorithms and an intuitive understanding of the underlying concepts is crucial for the success of the entire data science process. We will start with a gen作者: 蛛絲 時間: 2025-3-23 08:10 作者: blister 時間: 2025-3-23 11:46 作者: Chromatic 時間: 2025-3-23 17:54
Natural Language Processingnguages offers a plethora of benefits. Humans can do mathematical calculations, but when computers learn to do them, they can perform much more complex calculations much faster than humans would. Similarly, when computers learn human languages, they can process much more language data which opens up myriad possibilities.作者: Hectic 時間: 2025-3-23 19:48
Mathematics – Key Technology for the Futurenguages offers a plethora of benefits. Humans can do mathematical calculations, but when computers learn to do them, they can perform much more complex calculations much faster than humans would. Similarly, when computers learn human languages, they can process much more language data which opens up myriad possibilities.作者: 隨意 時間: 2025-3-23 22:43 作者: Criteria 時間: 2025-3-24 04:06
Legislative Political Representation,ail, sender’s email address, etc.; infer whether a digital payment transaction is “fraud” or “non-fraud” based on the details of the transaction like the location of the transaction, the amount and mode of payment, etc.作者: 我吃花盤旋 時間: 2025-3-24 09:40
Stephanie Knorr,Roland Pulch,Michael Günthergroup of objects that do not show these characteristics. Once we discern two such apparently distinct groups, we give them a name – . and . things. While this may seem like a simplistic example, similar groupings based on biological characteristics, evolution, etc., lead to various biological taxonomies.作者: Daily-Value 時間: 2025-3-24 12:48 作者: BUST 時間: 2025-3-24 14:49
Clusteringgroup of objects that do not show these characteristics. Once we discern two such apparently distinct groups, we give them a name – . and . things. While this may seem like a simplistic example, similar groupings based on biological characteristics, evolution, etc., lead to various biological taxonomies.作者: cylinder 時間: 2025-3-24 23:04 作者: FELON 時間: 2025-3-25 02:36
Data Preparation what day of the week it is, what month it is, etc. Hence, we transformed the data so that it contains the hour, day, month, etc., along with the corresponding aggregated sale amount hoping that it will enable ML algorithms to find such trends. Hence, preparing the data in such ways might result in 作者: 表示向下 時間: 2025-3-25 03:34 作者: Deduct 時間: 2025-3-25 08:49 作者: DECRY 時間: 2025-3-25 14:00 作者: maintenance 時間: 2025-3-25 16:50 作者: deface 時間: 2025-3-25 22:28 作者: ineptitude 時間: 2025-3-26 03:09
Legislative Political Representation,w observation belongs based on values of some observed attributes. For example, infer whether a mail is “spam” or “regular” based on the body of the mail, sender’s email address, etc.; infer whether a digital payment transaction is “fraud” or “non-fraud” based on the details of the transaction like 作者: CAGE 時間: 2025-3-26 04:48 作者: 抱狗不敢前 時間: 2025-3-26 11:39 作者: 錢財 時間: 2025-3-26 13:44
Stephanie Knorr,Roland Pulch,Michael Güntherin nature, we tend to divide them into two groups: one that is able to ingest food and convert it to energy, is able to reproduce etc. and the second group of objects that do not show these characteristics. Once we discern two such apparently distinct groups, we give them a name – . and . things. Wh作者: 疏遠(yuǎn)天際 時間: 2025-3-26 17:09
Stephanie Knorr,Roland Pulch,Michael Günthergs that are rarely seen; an unheard-of combination of symptoms/test readings, or a rare pattern in a medical image such as a CT scan; and network traffic in an IT system that is unusual, these are a few cases that tend to raise attention. Detecting any abnormal occurrences in the data is referred to作者: 金哥占卜者 時間: 2025-3-26 22:00
Stephanie Knorr,Roland Pulch,Michael Güntherprocess visual information. Under the overarching field of ., the field of computer vision is one of the more complex, higher levels of “intelligence.” The tremendous successes of deep learning approaches to computer vision resuscitated neural networks, data science, and AI in general, starting from作者: Sleep-Paralysis 時間: 2025-3-27 04:18 作者: confide 時間: 2025-3-27 06:44 作者: sundowning 時間: 2025-3-27 12:45
Some Problems of Classical Mathematics, dedicated to the ML algorithms/techniques you can use to build models and libraries that implement these algorithms. Awareness of different ML algorithms and an intuitive understanding of the underlying concepts is crucial for the success of the entire data science process. We will start with a gen作者: Mercantile 時間: 2025-3-27 16:10
Vineet Raina,Srinath KrishnamurthyComplete guide from the ground-up to building an effective data science practice.Lays out a reference architecture that can help ensure your data science team is productive.Builds the necessary intuit作者: 媒介 時間: 2025-3-27 20:11
http://image.papertrans.cn/b/image/191844.jpg作者: Extemporize 時間: 2025-3-27 22:43 作者: liposuction 時間: 2025-3-28 03:09 作者: Tonometry 時間: 2025-3-28 08:39
Computer Visionprocess visual information. Under the overarching field of ., the field of computer vision is one of the more complex, higher levels of “intelligence.” The tremendous successes of deep learning approaches to computer vision resuscitated neural networks, data science, and AI in general, starting from 2012.作者: comely 時間: 2025-3-28 11:38
Sequential Decision-Makingwith a view to gaining a desired outcome in the longer run. The “desired outcome” can take various forms – maximizing profits/rewards (e.g., in an investment strategy), maximizing the chances to realize a targeted goal (e.g., winning in a competition such as chess), or saving patients with life-threatening diseases.作者: 合并 時間: 2025-3-28 18:13 作者: preservative 時間: 2025-3-28 20:32 作者: blight 時間: 2025-3-29 01:09 作者: 溫室 時間: 2025-3-29 03:13 作者: 樣式 時間: 2025-3-29 07:51 作者: 摸索 時間: 2025-3-29 14:37 作者: hardheaded 時間: 2025-3-29 19:34
Platonic and Semi- Platonic Solids,Having touched upon data science in the context of your business, it is now time to determine what . of data science is best suited for your business. There are primarily two cultures of data science – the monastic culture (as defined and practiced by monks) and the wild-west culture (as iconized by cowboys).作者: 桶去微染 時間: 2025-3-29 21:22
Ronny S. Hansmann,Uwe T. ZimmermannOnce upon a time, you may have had a close friend recommending a book, song, or movie to you – since the friend knew your “tastes,” you would typically check out their recommendations.作者: Pcos971 時間: 2025-3-30 02:13
Rolf Rannacher,Vincent HeuvelineIn this chapter, we provide a very high-level overview of the various techniques and technologies used for data science. This brief overview is intended to establish the framework for specifics covered in Chapters 13–19.作者: oracle 時間: 2025-3-30 04:07
Jürgen Fuhrmann,Martin PetzoldtIn this chapter, we shall cover the typical techniques and technologies used in the data capture step of the data science process.作者: 強制性 時間: 2025-3-30 11:43 作者: Hla461 時間: 2025-3-30 15:21
Introduction: The Data , ProcessJune 1918. A subcommittee consisting of Prof. Eddington, Sir Dyson, and others made arrangements for expeditions to Sobral in North Brazil and to the island of Principe. The goal of these two expeditions? To collect some data during the eclipse that was to occur on 作者: V洗浴 時間: 2025-3-30 18:12
Data Science and Your BusinessHaving understood the data science process and what it entails, we now delve into the business-fitment considerations of data science.作者: Graphite 時間: 2025-3-31 00:08 作者: 字形刻痕 時間: 2025-3-31 02:43
