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Zero to Ai

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  • 00001 Chapter 1. An introduction to artificial intelligence.mp4
    09:06
  • 00002 Chapter 1. The engine of the AI revolution - machine learning.mp4
    05:19
  • 00003 Chapter 1. What is artificial intelligence after all.mp4
    06:45
  • 00004 Chapter 1. Our teaching method.mp4
    04:07
  • 00005 Part 1. Understanding AI.mp4
    01:48
  • 00006 Chapter 2. Artificial intelligence for core business data.mp4
    06:40
  • 00007 Chapter 2. Using AI with core business data.mp4
    06:10
  • 00008 Chapter 2. Adding AI capabilities to FutureHouse.mp4
    10:34
  • 00009 Chapter 2. The machine learning advantage.mp4
    09:00
  • 00010 Chapter 2. Case studies.mp4
    13:59
  • 00011 Chapter 2. How Square used AI to lend billions to small businesses.mp4
    12:23
  • 00012 Chapter 2. Evaluating performance and risk.mp4
    07:05
  • 00013 Chapter 3. AI for sales and marketing.mp4
    05:46
  • 00014 Chapter 3. Predicting churning customers.mp4
    09:16
  • 00015 Chapter 3. Using AI to boost conversion rates and upselling.mp4
    09:56
  • 00016 Chapter 3. Unsupervised learning or clustering.mp4
    08:53
  • 00017 Chapter 3. Unsupervised learning for customer segmentation.mp4
    06:10
  • 00018 Chapter 3. Measuring performance.mp4
    09:42
  • 00019 Chapter 3. Tying ML metrics to business outcomes and risks.mp4
    05:45
  • 00020 Chapter 3. Case studies.mp4
    10:47
  • 00021 Chapter 3. AI to anticipate customer needs - Target.mp4
    09:57
  • 00022 Chapter 4. AI for media.mp4
    08:20
  • 00023 Chapter 4. Using AI for image classification - deep learning.mp4
    08:14
  • 00024 Chapter 4. Using transfer learning with small datasets.mp4
    10:07
  • 00025 Chapter 4. Using content generation and style transfer.mp4
    12:36
  • 00026 Chapter 4. Case study - optimizing agriculture with deep learning.mp4
    10:14
  • 00027 Chapter 5. AI for natural language.mp4
    05:26
  • 00028 Chapter 5. Breaking down NLP - Measuring complexity.mp4
    05:51
  • 00029 Chapter 5. Adding NLP capabilities to your organization.mp4
    05:12
  • 00030 Chapter 5. Sentiment analysis.mp4
    07:23
  • 00031 Chapter 5. From sentiment analysis to text classification.mp4
    07:16
  • 00032 Chapter 5. Scoping a NLP classification project.mp4
    06:05
  • 00033 Chapter 5. Natural conversation.mp4
    08:26
  • 00034 Chapter 5. Designing products that overcome technology limitations.mp4
    05:24
  • 00035 Chapter 5. Case study - Translated.mp4
    09:57
  • 00036 Chapter 5. Case questions.mp4
    07:44
  • 00037 Chapter 6. AI for content curation and community building.mp4
    10:34
  • 00038 Chapter 6. Content-based systems beyond simple features.mp4
    08:35
  • 00039 Chapter 6. The wisdom of crowds - collaborative filtering.mp4
    07:53
  • 00040 Chapter 6. Recommendations gone wrong.mp4
    06:10
  • 00041 Chapter 6. Netflix s recommender system.mp4
    06:18
  • 00042 Chapter 6. The business value of recommendations.mp4
    08:38
  • 00043 Part 2. Building AI.mp4
    01:15
  • 00044 Chapter 7. Ready finding AI opportunities.mp4
    14:49
  • 00045 Chapter 7. Invention - Scouting for AI opportunities.mp4
    07:28
  • 00046 Chapter 7. Prioritization - Evaluating AI projects.mp4
    11:13
  • 00047 Chapter 7. Validation - Analyzing risks.mp4
    07:21
  • 00048 Chapter 7. Deconstructing an AI product.mp4
    13:03
  • 00049 Chapter 7. Translating an AI project into ML-friendly terms.mp4
    11:47
  • 00050 Chapter 7. Exercises.mp4
    12:26
  • 00051 Chapter 8. Set preparing data technology and people.mp4
    04:20
  • 00052 Chapter 8. Where do I get data.mp4
    13:02
  • 00053 Chapter 8. How much data do I need.mp4
    07:46
  • 00054 Chapter 8. Data quality.mp4
    08:34
  • 00055 Chapter 8. Recruiting an AI team.mp4
    11:12
  • 00056 Chapter 9. Go AI implementation strategy.mp4
    08:34
  • 00057 Chapter 9. The Borrow option - ML platforms.mp4
    09:34
  • 00058 Chapter 9. Using the Lean Strategy.mp4
    10:13
  • 00059 Chapter 9. Doing things yourself - Build solutions.mp4
    05:01
  • 00060 Chapter 9. Understanding the virtuous cycle of AI.mp4
    09:56
  • 00061 Chapter 9. Managing AI projects.mp4
    06:36
  • 00062 Chapter 9. When AI fails.mp4
    10:34
  • 00063 Chapter 9. Emotional diary.mp4
    06:58
  • 00064 Chapter 10. What lies ahead.mp4
    11:50
  • 00065 Chapter 10. AI and jobs.mp4
    10:35
  • 00066 Chapter 10. When AI fails - Corner cases and adversarial attacks.mp4
    07:29
  • 00067 Chapter 10. Opportunities for AI in society.mp4
    07:02
  • 00068 Chapter 10. Opportunities for AI in industries.mp4
    07:52
  • 00069 Chapter 10. Health care.mp4
    12:18
  • 00070 Chapter 10. Manufacturing.mp4
    09:40
  • 00071 Chapter 10. What about general AI.mp4
    06:19
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    Manning Publications is an American publisher specializing in content relating to computers. Manning mainly publishes textbooks but also release videos and projects for professionals within the computing world.
    • language english
    • Training sessions 71
    • duration 10:00:18
    • Release Date 2023/11/06