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[FCSNEW.NET] Udemy - The AI Engineer Course 2025 Complete AI Engineer Bootcamp

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FCSNEW NET Udemy - The AI Engineer Course 2025 Complete AI Engineer Bootcamp

文件列表
  1. 01. Intro to AI Module Getting started/1. Building an AI tool in 5 minutes A quick demo.mp444.96MB
  2. 01. Intro to AI Module Getting started/2. What does the course cover.mp420.67MB
  3. 01. Intro to AI Module Getting started/3. Natural vs Artificial Intelligence.mp443.79MB
  4. 01. Intro to AI Module Getting started/4. Brief history of AI.mp495.31MB
  5. 01. Intro to AI Module Getting started/5. Demystifying AI, Data science, Machine learning, and Deep learning.mp447.95MB
  6. 01. Intro to AI Module Getting started/6. Weak vs Strong AI.mp454.74MB
  7. 02. Intro to AI Module Data is essential for building AI/1. Structured vs unstructured data.mp437.71MB
  8. 02. Intro to AI Module Data is essential for building AI/2. How we collect data.mp479.78MB
  9. 02. Intro to AI Module Data is essential for building AI/3. Labelled and unlabelled data.mp444.52MB
  10. 02. Intro to AI Module Data is essential for building AI/4. Metadata Data that describes data.mp435.41MB
  11. 03. Intro to AI Module Key AI techniques/1. Machine learning.mp4119.75MB
  12. 03. Intro to AI Module Key AI techniques/2. Supervised, Unsupervised, and Reinforcement learning.mp4113.42MB
  13. 03. Intro to AI Module Key AI techniques/3. Deep learning.mp4159.86MB
  14. 04. Intro to AI Module Important AI branches/1. Robotics.mp493.33MB
  15. 04. Intro to AI Module Important AI branches/2. Computer vision.mp493.32MB
  16. 04. Intro to AI Module Important AI branches/3. Traditional ML.mp426.8MB
  17. 04. Intro to AI Module Important AI branches/4. Generative AI.mp482.38MB
  18. 05. Intro to AI Module Understanding Generative AI/1. The rise of Gen AI Introducing ChatGPT.mp444.34MB
  19. 05. Intro to AI Module Understanding Generative AI/10. Buy vs Make foundation models vs private models.mp453.31MB
  20. 05. Intro to AI Module Understanding Generative AI/2. Early approaches to Natural Language Processing (NLP).mp452.33MB
  21. 05. Intro to AI Module Understanding Generative AI/3. Recent NLP advancements.mp460.28MB
  22. 05. Intro to AI Module Understanding Generative AI/4. From Language Models to Large Language Models (LLMs).mp4129.18MB
  23. 05. Intro to AI Module Understanding Generative AI/5. The efficiency of LLM training. Supervised vs Semi-supervised learning.mp470.82MB
  24. 05. Intro to AI Module Understanding Generative AI/6. From N-Grams to RNNs to Transformers The Evolution of NLP.mp4106.29MB
  25. 05. Intro to AI Module Understanding Generative AI/7. Phases in building LLMs.mp494.94MB
  26. 05. Intro to AI Module Understanding Generative AI/8. Prompt engineering vs Fine-tuning vs RAG Techniques for AI optimization.mp486.42MB
  27. 05. Intro to AI Module Understanding Generative AI/9. The importance of foundation models.mp457.59MB
  28. 06. Intro to AI Module Practical challenges in Generative AI/1. Inconsistency and hallucination.mp456.75MB
  29. 06. Intro to AI Module Practical challenges in Generative AI/2. Budgeting and API costs.mp461MB
  30. 06. Intro to AI Module Practical challenges in Generative AI/3. Latency.mp429.57MB
  31. 06. Intro to AI Module Practical challenges in Generative AI/4. Running out of data.mp450.11MB
  32. 07. Intro to AI Module The AI tech stack/1. Python programming.mp443.79MB
  33. 07. Intro to AI Module The AI tech stack/2. Working with APIs.mp432.53MB
  34. 07. Intro to AI Module The AI tech stack/3. Vector databases.mp461.63MB
  35. 07. Intro to AI Module The AI tech stack/4. The importance of open source.mp4124.73MB
  36. 07. Intro to AI Module The AI tech stack/5. Hugging Face.mp436.07MB
  37. 07. Intro to AI Module The AI tech stack/6. LangChain.mp458.91MB
  38. 07. Intro to AI Module The AI tech stack/7. AI evaluation tools.mp463.56MB
  39. 08. Intro to AI Module AI job positions/1. AI strategist.mp4105.35MB
  40. 08. Intro to AI Module AI job positions/2. AI developer.mp491.09MB
  41. 08. Intro to AI Module AI job positions/3. AI engineer.mp478.76MB
  42. 09. Intro to AI Module Looking ahead/1. AI ethics.mp4116.3MB
  43. 09. Intro to AI Module Looking ahead/2. Future of AI.mp495.68MB
  44. 10. Python Module Why Python/1. Programming Explained in a Few Minutes.mp446.96MB
  45. 10. Python Module Why Python/2. Why Python.mp445.85MB
  46. 11. Python Module Setting Up the Environment/1. Jupyter - Introduction.mp432.46MB
  47. 11. Python Module Setting Up the Environment/2. Jupyter - Installing Anaconda.mp426.11MB
  48. 11. Python Module Setting Up the Environment/3. Jupyter - Introduction to Using Jupyter.mp412.1MB
  49. 11. Python Module Setting Up the Environment/4. Jupyter - Working with Notebook Files.mp423.72MB
  50. 11. Python Module Setting Up the Environment/5. Jupyter - Using Shortcuts.mp417.33MB
  51. 11. Python Module Setting Up the Environment/6. Jupyter - Handling Error Messages.mp440.31MB
  52. 11. Python Module Setting Up the Environment/7. Jupyter - Restarting the Kernel.mp48.36MB
  53. 12. Python Module Python Variables and Data Types/1. Python Variables.mp414.07MB
  54. 12. Python Module Python Variables and Data Types/14. Types of Data - Strings.mp424.11MB
  55. 12. Python Module Python Variables and Data Types/7. Types of Data - Numbers and Boolean Values.mp413.7MB
  56. 13. Python Module Basic Python Syntax/1. Basic Python Syntax - Arithmetic Operators.mp415.44MB
  57. 13. Python Module Basic Python Syntax/11. Basic Python Syntax - The Double Equality Sign.mp44.95MB
  58. 13. Python Module Basic Python Syntax/14. Basic Python Syntax - Reassign Values.mp43.34MB
  59. 13. Python Module Basic Python Syntax/20. Basic Python Syntax - Add Comments.mp44.67MB
  60. 13. Python Module Basic Python Syntax/22. Basic Python Syntax - Line Continuation.mp42.11MB
  61. 13. Python Module Basic Python Syntax/24. Basic Python Syntax - Indexing Elements.mp44.86MB
  62. 13. Python Module Basic Python Syntax/28. Basic Python Syntax - Indentation.mp45.46MB
  63. 14. Python Module More on Operators/1. Operators - Comparison Operators.mp48.22MB
  64. 14. Python Module More on Operators/7. Operators - Logical and Identity Operators.mp424.08MB
  65. 15. Python Module Conditional Statements/1. Conditional Statements - The IF Statement.mp410.8MB
  66. 15. Python Module Conditional Statements/10. Conditional Statements - A Note on Boolean Values.mp48.89MB
  67. 15. Python Module Conditional Statements/5. Conditional Statements - The ELSE Statement.mp410.82MB
  68. 15. Python Module Conditional Statements/7. Conditional Statements - The ELIF Statement.mp425.06MB
  69. 16. Python Module Functions/1. Functions - Defining a Function in Python.mp46.28MB
  70. 16. Python Module Functions/11. Functions - Creating Functions Containing a Few Arguments.mp46.02MB
  71. 16. Python Module Functions/12. Functions - Notable Built-in Functions in Python.mp417.85MB
  72. 16. Python Module Functions/2. Functions - Creating a Function with a Parameter.mp418.08MB
  73. 16. Python Module Functions/5. Functions - Another Way to Define a Function.mp411.14MB
  74. 16. Python Module Functions/7. Functions - Using a Function in Another Function.mp46.49MB
  75. 16. Python Module Functions/9. Functions - Combining Conditional Statements and Functions.mp413.06MB
  76. 17. Python Module Sequences/1. Sequences - Lists.mp417.63MB
  77. 17. Python Module Sequences/14. Sequences - List Slicing.mp423.96MB
  78. 17. Python Module Sequences/22. Sequences - Tuples.mp413.5MB
  79. 17. Python Module Sequences/27. Sequences - Dictionaries.mp419.23MB
  80. 17. Python Module Sequences/8. Sequences - Using Methods.mp417.3MB
  81. 18. Python Module Iteration/1. Iteration - For Loops.mp411.55MB
  82. 18. Python Module Iteration/12. Iteraion - Use Conditional Statements and Loops Together.mp412.61MB
  83. 18. Python Module Iteration/16. Iteration - Conditional Statements, Functions, and Loops.mp48.15MB
  84. 18. Python Module Iteration/18. Iteration - Iterating over Dictionaries.mp413.44MB
  85. 18. Python Module Iteration/5. Iteration - While Loops and Incrementing.mp413.03MB
  86. 18. Python Module Iteration/7. Iteration - Creatie Lists with the range() Function.mp414.68MB
  87. 19. Python Module A Few Important Python Concepts and Terms/1. Introduction to Object Oriented Programming (OOP).mp428.17MB
  88. 19. Python Module A Few Important Python Concepts and Terms/2. Modules, Packages, and the Python Standard Library.mp442.74MB
  89. 19. Python Module A Few Important Python Concepts and Terms/3. Importing Modules.mp413.17MB
  90. 19. Python Module A Few Important Python Concepts and Terms/5. What is Software Documentation.mp442.87MB
  91. 19. Python Module A Few Important Python Concepts and Terms/6. The Python Documentation.mp450.41MB
  92. 20. NLP Module Introduction/1. Introduction to the course.mp454.54MB
  93. 20. NLP Module Introduction/3. Introduction to NLP.mp432.62MB
  94. 20. NLP Module Introduction/4. NLP in everyday life.mp418.95MB
  95. 20. NLP Module Introduction/5. Supervised vs unsupervised NLP.mp426.26MB
  96. 21. NLP Module Text Preprocessing/1. The importance of data preparation.mp433.81MB
  97. 21. NLP Module Text Preprocessing/10. Practical task.mp460.6MB
  98. 21. NLP Module Text Preprocessing/2. Lowercase.mp49.37MB
  99. 21. NLP Module Text Preprocessing/3. Removing stop words.mp419.79MB
  100. 21. NLP Module Text Preprocessing/4. Regular expressions.mp440.65MB
  101. 21. NLP Module Text Preprocessing/5. Tokenization.mp410.22MB
  102. 21. NLP Module Text Preprocessing/6. Stemming.mp47.14MB
  103. 21. NLP Module Text Preprocessing/7. Lemmatization.mp410.71MB
  104. 21. NLP Module Text Preprocessing/8. N-grams.mp418.17MB
  105. 22. NLP Module Identifying Parts of Speech and Named Entities/1. Text tagging.mp423MB
  106. 22. NLP Module Identifying Parts of Speech and Named Entities/2. Parts of Speech (POS) tagging.mp421.24MB
  107. 22. NLP Module Identifying Parts of Speech and Named Entities/3. Named Entity Recognition (NER).mp424.03MB
  108. 22. NLP Module Identifying Parts of Speech and Named Entities/5. Practical task.mp456.63MB
  109. 23. NLP Module Sentiment Analysis/1. What is sentiment analysis.mp437.13MB
  110. 23. NLP Module Sentiment Analysis/2. Rule-based sentiment analysis.mp422.79MB
  111. 23. NLP Module Sentiment Analysis/3. Pre-trained transformer models.mp425.91MB
  112. 23. NLP Module Sentiment Analysis/5. Practical task.mp431.75MB
  113. 24. NLP Module Vectorizing Text/1. Numerical representation of text.mp433.26MB
  114. 24. NLP Module Vectorizing Text/2. Bag of Words model.mp411.52MB
  115. 24. NLP Module Vectorizing Text/3. TF-IDF.mp419.02MB
  116. 25. NLP Module Topic Modelling/1. What is topic modelling.mp456.91MB
  117. 25. NLP Module Topic Modelling/2. When to use topic modelling.mp431.27MB
  118. 25. NLP Module Topic Modelling/3. Latent Dirichlet Allocation (LDA).mp444.65MB
  119. 25. NLP Module Topic Modelling/5. LDA in Python.mp430.03MB
  120. 25. NLP Module Topic Modelling/6. Latent Semantic Analysis (LSA).mp432.98MB
  121. 25. NLP Module Topic Modelling/7. LSA in Python.mp413.38MB
  122. 25. NLP Module Topic Modelling/8. How many topics.mp429.88MB
  123. 26. NLP Module Building Your Own Text Classifier/1. Building a custom text classifier.mp418.79MB
  124. 26. NLP Module Building Your Own Text Classifier/2. Logistic regression.mp426.55MB
  125. 26. NLP Module Building Your Own Text Classifier/3. Naive Bayes.mp48.43MB
  126. 26. NLP Module Building Your Own Text Classifier/4. Linear support vector machine.mp411.41MB
  127. 27. NLP Module Categorizing Fake News (Case Study)/2. Introducing the project.mp418.15MB
  128. 27. NLP Module Categorizing Fake News (Case Study)/3. Exploring our data through POS tags.mp437.99MB
  129. 27. NLP Module Categorizing Fake News (Case Study)/4. Extracting named entities.mp419.06MB
  130. 27. NLP Module Categorizing Fake News (Case Study)/5. Processing the text.mp455.12MB
  131. 27. NLP Module Categorizing Fake News (Case Study)/6. Does sentiment differ between news types.mp420.37MB
  132. 27. NLP Module Categorizing Fake News (Case Study)/7. What topics appear in fake news (Part 1).mp425.03MB
  133. 27. NLP Module Categorizing Fake News (Case Study)/8. What topics appear in fake news (Part 2).mp434.46MB
  134. 27. NLP Module Categorizing Fake News (Case Study)/9. Categorizing fake news with a custom classifier.mp430.82MB
  135. 28. NLP Module The Future of NLP/1. What is deep learning.mp452.54MB
  136. 28. NLP Module The Future of NLP/2. Deep learning for NLP.mp439.16MB
  137. 28. NLP Module The Future of NLP/3. Non-English NLP.mp438.47MB
  138. 28. NLP Module The Future of NLP/4. What's next for NLP.mp429.73MB
  139. 29. LLMs Module Introduction to Large Language Models/1. Introduction to the course.mp449.41MB
  140. 29. LLMs Module Introduction to Large Language Models/3. What are LLMs.mp463.8MB
  141. 29. LLMs Module Introduction to Large Language Models/4. How large is an LLM.mp460.84MB
  142. 29. LLMs Module Introduction to Large Language Models/5. General purpose models.mp424.23MB
  143. 29. LLMs Module Introduction to Large Language Models/6. Pre-training and fine tuning.mp451.47MB
  144. 29. LLMs Module Introduction to Large Language Models/7. What can LLMs be used for.mp471.21MB
  145. 30. LLMs Module The Transformer Architecture/1. Deep learning recap.mp453.07MB
  146. 30. LLMs Module The Transformer Architecture/2. The problem with RNNs.mp477.18MB
  147. 30. LLMs Module The Transformer Architecture/3. The solution attention is all you need.mp457.7MB
  148. 30. LLMs Module The Transformer Architecture/4. The transformer architecture.mp421.81MB
  149. 30. LLMs Module The Transformer Architecture/5. Input embeddings.mp461.14MB
  150. 30. LLMs Module The Transformer Architecture/6. Multi-headed attention.mp486.92MB
  151. 30. LLMs Module The Transformer Architecture/7. Feed-forward layer.mp455.65MB
  152. 30. LLMs Module The Transformer Architecture/8. Masked multihead attention.mp429.71MB
  153. 30. LLMs Module The Transformer Architecture/9. Predicting the final outputs.mp436.15MB
  154. 31. LLMs Module Getting Started With GPT Models/1. What does GPT mean.mp430.91MB
  155. 31. LLMs Module Getting Started With GPT Models/10. Adding custom data to our chatbot.mp424.44MB
  156. 31. LLMs Module Getting Started With GPT Models/2. The development of ChatGPT.mp453.57MB
  157. 31. LLMs Module Getting Started With GPT Models/3. OpenAI API.mp418.04MB
  158. 31. LLMs Module Getting Started With GPT Models/4. Generating text.mp411.2MB
  159. 31. LLMs Module Getting Started With GPT Models/5. Customizing GPT output.mp425.32MB
  160. 31. LLMs Module Getting Started With GPT Models/6. Key word text summarization.mp445.71MB
  161. 31. LLMs Module Getting Started With GPT Models/7. Coding a simple chatbot.mp444.39MB
  162. 31. LLMs Module Getting Started With GPT Models/8. Introduction to LangChain in Python.mp418.11MB
  163. 31. LLMs Module Getting Started With GPT Models/9. LangChain.mp459.67MB
  164. 32. LLMs Module Hugging Face Transformers/1. Hugging Face package.mp457.92MB
  165. 32. LLMs Module Hugging Face Transformers/2. The transformer pipeline.mp444.49MB
  166. 32. LLMs Module Hugging Face Transformers/3. Pre-trained tokenizers.mp455.7MB
  167. 32. LLMs Module Hugging Face Transformers/4. Special tokens.mp461.08MB
  168. 32. LLMs Module Hugging Face Transformers/5. Hugging Face and PyTorchTensorFlow.mp424.88MB
  169. 32. LLMs Module Hugging Face Transformers/6. Saving and loading models.mp49.97MB
  170. 33. LLMs Module Question and Answer Models With BERT/1. GPT vs BERT.mp465.29MB
  171. 33. LLMs Module Question and Answer Models With BERT/2. BERT architecture.mp499.25MB
  172. 33. LLMs Module Question and Answer Models With BERT/3. Loading the model and tokenizer.mp47.29MB
  173. 33. LLMs Module Question and Answer Models With BERT/4. BERT embeddings.mp429.67MB
  174. 33. LLMs Module Question and Answer Models With BERT/5. Calculating the response.mp438.99MB
  175. 33. LLMs Module Question and Answer Models With BERT/6. Creating a QA bot.mp478.38MB
  176. 33. LLMs Module Question and Answer Models With BERT/7. BERT, RoBERTa, DistilBERT.mp449.57MB
  177. 34. LLMs Module Text Classification With XLNet/1. GPT vs BERT vs XLNET.mp487.58MB
  178. 34. LLMs Module Text Classification With XLNet/3. Preprocessing our data.mp468.32MB
  179. 34. LLMs Module Text Classification With XLNet/4. XLNet Embeddings.mp428.92MB
  180. 34. LLMs Module Text Classification With XLNet/5. Fine tuning XLNet.mp425.29MB
  181. 34. LLMs Module Text Classification With XLNet/6. Evaluating our model.mp420.51MB
  182. 35. LangChain Module Introduction/1. Introduction to the course.mp460.67MB
  183. 35. LangChain Module Introduction/3. Business applications of LangChain.mp464.32MB
  184. 35. LangChain Module Introduction/4. What makes LangChain powerful.mp451.33MB
  185. 35. LangChain Module Introduction/5. What does the course cover.mp460.31MB
  186. 36. LangChain Module Tokens, Models, and Prices/1. Tokens.mp445.62MB
  187. 36. LangChain Module Tokens, Models, and Prices/2. Models and Prices.mp445.2MB
  188. 37. LangChain Module Setting Up the Environment/1. Setting up a custom anaconda environment for Jupyter integration.mp415.73MB
  189. 37. LangChain Module Setting Up the Environment/2. Obtaining an OpenAI API key.mp414.03MB
  190. 37. LangChain Module Setting Up the Environment/3. Setting the API key as an environment variable.mp448.14MB
  191. 38. LangChain Module The OpenAI API/1. First Steps.mp428.12MB
  192. 38. LangChain Module The OpenAI API/2. System, user, and assistant roles.mp436.22MB
  193. 38. LangChain Module The OpenAI API/3. Creating a sarcastic chatbot.mp418.29MB
  194. 38. LangChain Module The OpenAI API/4. Temperature, max tokens, and streaming.mp466.88MB
  195. 39. LangChain Module Model Inputs/1. The LangChain framework.mp463.14MB
  196. 39. LangChain Module Model Inputs/2. ChatOpenAI.mp441.7MB
  197. 39. LangChain Module Model Inputs/3. System and human messages.mp435.36MB
  198. 39. LangChain Module Model Inputs/4. AI messages.mp433.55MB
  199. 39. LangChain Module Model Inputs/5. Prompt templates and prompt values.mp426.81MB
  200. 39. LangChain Module Model Inputs/6. Chat prompt templates and chat prompt values.mp442.13MB
  201. 39. LangChain Module Model Inputs/7. Few-shot chat message prompt templates.mp448.76MB
  202. 39. LangChain Module Model Inputs/8. LLMChain.mp419.63MB
  203. 40. LangChain Module Message History and Chatbot Memory/1. Chat message history.mp433.07MB
  204. 40. LangChain Module Message History and Chatbot Memory/2. Conversation buffer memory Implementing the setup.mp424.15MB
  205. 40. LangChain Module Message History and Chatbot Memory/3. Conversation buffer memory Configuring the chain.mp446.63MB
  206. 40. LangChain Module Message History and Chatbot Memory/4. Conversation buffer window memory.mp433.3MB
  207. 40. LangChain Module Message History and Chatbot Memory/5. Conversation summary memory.mp461.7MB
  208. 40. LangChain Module Message History and Chatbot Memory/6. Combined memory.mp436.61MB
  209. 41. LangChain Module Output Parsers/1. String output parser.mp413.7MB
  210. 41. LangChain Module Output Parsers/2. Comma-separated list output parser.mp418.41MB
  211. 41. LangChain Module Output Parsers/3. Datetime output parser.mp420.72MB
  212. 42. LangChain Module LangChain Expression Language (LCEL)/1. Piping a prompt, model, and an output parser.mp438.63MB
  213. 42. LangChain Module LangChain Expression Language (LCEL)/10. The @chain decorator.mp420.43MB
  214. 42. LangChain Module LangChain Expression Language (LCEL)/11. Adding memory to a chain (Part 1) Implementing the setup.mp423.48MB
  215. 42. LangChain Module LangChain Expression Language (LCEL)/12. RunnablePassthrough with additional keys.mp428.96MB
  216. 42. LangChain Module LangChain Expression Language (LCEL)/13. Itemgetter.mp417.98MB
  217. 42. LangChain Module LangChain Expression Language (LCEL)/14. Adding memory to a chain (Part 2) Creating the chain.mp452.97MB
  218. 42. LangChain Module LangChain Expression Language (LCEL)/2. Batching.mp434.01MB
  219. 42. LangChain Module LangChain Expression Language (LCEL)/3. Streaming.mp427.98MB
  220. 42. LangChain Module LangChain Expression Language (LCEL)/4. The Runnable and RunnableSequence classes.mp439.93MB
  221. 42. LangChain Module LangChain Expression Language (LCEL)/5. Piping chains and the RunnablePassthrough class.mp442.76MB
  222. 42. LangChain Module LangChain Expression Language (LCEL)/6. Graphing Runnables.mp411.68MB
  223. 42. LangChain Module LangChain Expression Language (LCEL)/7. RunnableParallel.mp436.34MB
  224. 42. LangChain Module LangChain Expression Language (LCEL)/8. Piping a RunnableParallel with other Runnables.mp444.7MB
  225. 42. LangChain Module LangChain Expression Language (LCEL)/9. RunnableLambda.mp422.25MB
  226. 43. LangChain Module Retrieval Augmented Generation (RAG)/1. How to integrate custom data into an LLM.mp448.59MB
  227. 43. LangChain Module Retrieval Augmented Generation (RAG)/10. Indexing Document splitting with Markdown header text splitter.mp444.78MB
  228. 43. LangChain Module Retrieval Augmented Generation (RAG)/11. Indexing Text embedding with OpenAI.mp442.42MB
  229. 43. LangChain Module Retrieval Augmented Generation (RAG)/12. Indexing Creating a Chroma vectorstore.mp433.42MB
  230. 43. LangChain Module Retrieval Augmented Generation (RAG)/13. Indexing Inspecting and managing documents in a vectorstore.mp427.98MB
  231. 43. LangChain Module Retrieval Augmented Generation (RAG)/14. Retrieval Similarity search.mp446.91MB
  232. 43. LangChain Module Retrieval Augmented Generation (RAG)/15. Retrieval Maximal Marginal Relevance (MMR) search.mp470.32MB
  233. 43. LangChain Module Retrieval Augmented Generation (RAG)/16. Retrieval Vectorstore-backed retriever.mp425.65MB
  234. 43. LangChain Module Retrieval Augmented Generation (RAG)/17. Generation Stuffing documents.mp428.55MB
  235. 43. LangChain Module Retrieval Augmented Generation (RAG)/18. Generation Generating a response.mp439.07MB
  236. 43. LangChain Module Retrieval Augmented Generation (RAG)/2. Introduction to RAG.mp442.79MB
  237. 43. LangChain Module Retrieval Augmented Generation (RAG)/3. Introduction to document loading and splitting.mp445.31MB
  238. 43. LangChain Module Retrieval Augmented Generation (RAG)/4. Introduction to document embedding.mp459.71MB
  239. 43. LangChain Module Retrieval Augmented Generation (RAG)/5. Introduction to document storing, retrieval, and generation.mp443.79MB
  240. 43. LangChain Module Retrieval Augmented Generation (RAG)/6. Indexing Document loading with PyPDFLoader.mp459.74MB
  241. 43. LangChain Module Retrieval Augmented Generation (RAG)/7. Indexing Document loading with Docx2txtLoader.mp417.71MB
  242. 43. LangChain Module Retrieval Augmented Generation (RAG)/8. Indexing Document splitting with character text splitter (Theory).mp424.26MB
  243. 43. LangChain Module Retrieval Augmented Generation (RAG)/9. Indexing Document splitting with character text splitter (Code along).mp433.38MB
  244. 44. LangChain Module Tools and Agents/1. Introduction to reasoning chatbots.mp439.56MB
  245. 44. LangChain Module Tools and Agents/2. Tools, toolkits, agents, and agent executors.mp458.84MB
  246. 44. LangChain Module Tools and Agents/4. Creating a Wikipedia tool and piping it to a chain.mp434.76MB
  247. 44. LangChain Module Tools and Agents/5. Creating a retriever and a custom tool.mp428.54MB
  248. 44. LangChain Module Tools and Agents/6. LangChain hub.mp425.29MB
  249. 44. LangChain Module Tools and Agents/7. Creating a tool calling agent and an agent executor.mp447.89MB
  250. 44. LangChain Module Tools and Agents/8. AgentAction and AgentFinish.mp439.34MB
  251. 45. Vector Databases Module Introduction/1. Introduction to the course.mp437.05MB
  252. 45. Vector Databases Module Introduction/3. Database comparison SQL, NoSQL, and Vector.mp459.66MB
  253. 45. Vector Databases Module Introduction/4. Understanding vector databases.mp450.4MB
  254. 46. Vector Databases Module Basics of Vector Space and High-Dimensional Data/1. Introduction to vector space.mp452.68MB
  255. 46. Vector Databases Module Basics of Vector Space and High-Dimensional Data/2. Distance metrics in vector space.mp463.98MB
  256. 46. Vector Databases Module Basics of Vector Space and High-Dimensional Data/3. Vector embeddings walkthrough.mp432.07MB
  257. 47. Vector Databases Module Introduction to The Pinecone Vector Database/1. Vector databases, comparison.mp475.96MB
  258. 47. Vector Databases Module Introduction to The Pinecone Vector Database/2. Pinecone registration, walkthrough and creating an Index.mp424.23MB
  259. 47. Vector Databases Module Introduction to The Pinecone Vector Database/3. Connecting to Pinecone using Python.mp414.18MB
  260. 47. Vector Databases Module Introduction to The Pinecone Vector Database/5. Creating and deleting a Pinecone index using Python.mp419.57MB
  261. 47. Vector Databases Module Introduction to The Pinecone Vector Database/6. Upserting data to a pinecone vector database.mp426.84MB
  262. 47. Vector Databases Module Introduction to The Pinecone Vector Database/7. Getting to know the fine web data set and loading it to Jupyter.mp422.04MB
  263. 47. Vector Databases Module Introduction to The Pinecone Vector Database/8. Upserting data from a text file and using an embedding algorithm.mp441.41MB
  264. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/1. Introduction to semantic search.mp431.36MB
  265. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/10. Data preprocessing and embedding for courses with section data.mp424.47MB
  266. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/12. Upserting the new updated files to Pinecone.mp415.54MB
  267. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/13. Similarity search and querying courses and sections data.mp445.16MB
  268. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/15. Using the BERT embedding algorithm.mp443.87MB
  269. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/16. Vector database for recommendation engines.mp445.05MB
  270. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/17. Vector database for semantic image search.mp449.09MB
  271. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/18. Vector database for biomedical research.mp433.6MB
  272. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/2. Introduction to the case study – smart search for data science courses.mp448.2MB
  273. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/3. Getting to know the data for the case study.mp432.2MB
  274. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/4. Data loading and preprocessing.mp422.8MB
  275. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/5. Pinecone Python APIs and connecting to the Pinecone server.mp427.1MB
  276. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/6. Embedding Algorithms.mp435.73MB
  277. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/7. Embedding the data and upserting the files to Pinecone.mp420.37MB
  278. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/8. Similarity search and querying the data.mp433.29MB
  279. 48. Vector Databases Module Semantic Search with Pinecone and Custom (Case Study)/9. How to update and change your vector database.mp441.39MB
  280. 49. Speech Recognition Module Introduction/1. Welcome to the world of Speech Recognition.mp476.29MB
  281. 49. Speech Recognition Module Introduction/3. Course Approach.mp463.21MB
  282. 49. Speech Recognition Module Introduction/4. How it all started Formants, harmonics, and phonemes.mp449.16MB
  283. 49. Speech Recognition Module Introduction/5. Development and Evolution.mp443.07MB
  284. 50. Speech Recognition Module Sound and Speech Basics/1. How do humans recognize speech.mp441.07MB
  285. 50. Speech Recognition Module Sound and Speech Basics/2. Fundamentals of sound and sound waves.mp450.8MB
  286. 50. Speech Recognition Module Sound and Speech Basics/3. Properties of sound waves.mp473MB
  287. 51. Speech Recognition Module Analog to Digital Conversion/1. Key concepts Sample Rate, bit depth, and bit rate.mp451.32MB
  288. 51. Speech Recognition Module Analog to Digital Conversion/2. Audio signal processing for Machine Learning and AI.mp468.6MB
  289. 52. Speech Recognition Module Audio Feature Extraction for AI Applications/1. Time-domain audio features.mp475.07MB
  290. 52. Speech Recognition Module Audio Feature Extraction for AI Applications/2. Frequency-domain and time-frequency-domain audio features.mp478.9MB
  291. 52. Speech Recognition Module Audio Feature Extraction for AI Applications/3. Time-domain feature extraction Framing and feature computation.mp453.45MB
  292. 52. Speech Recognition Module Audio Feature Extraction for AI Applications/4. Frequency-domain feature extraction Fourier transform.mp461.95MB
  293. 53. Speech Recognition Module Technology Mechanics/1. Acoustic and language modeling.mp445.94MB
  294. 53. Speech Recognition Module Technology Mechanics/2. Hidden Markov Models (HMMs) and traditional neural networks.mp465.74MB
  295. 53. Speech Recognition Module Technology Mechanics/3. Deep learning models CNNs, RNNs, and LSTMs.mp472.03MB
  296. 53. Speech Recognition Module Technology Mechanics/4. Advanced speech recognition systems Transformers.mp452.45MB
  297. 53. Speech Recognition Module Technology Mechanics/5. Building a speech recognition model part I.mp452.94MB
  298. 53. Speech Recognition Module Technology Mechanics/6. Building a speech recognition model part II.mp457.87MB
  299. 53. Speech Recognition Module Technology Mechanics/7. Selecting the appropriate speech recognition tool.mp473.18MB
  300. 54. Speech Recognition Module Setting Up the Environment/1. Installing Anaconda.mp416.89MB
  301. 54. Speech Recognition Module Setting Up the Environment/2. Setting up a new environment.mp424.9MB
  302. 54. Speech Recognition Module Setting Up the Environment/3. Installing packages for speech recognition.mp464.99MB
  303. 54. Speech Recognition Module Setting Up the Environment/4. Importing the relevant packages in Jupyter.mp414.99MB
  304. 55. Speech Recognition Module Transcribing Audio with Google Web Speech API/1. Audio file formats for speech recognition.mp473.04MB
  305. 55. Speech Recognition Module Transcribing Audio with Google Web Speech API/2. Importing audio files in Jupyter Notebook.mp452.03MB
  306. 55. Speech Recognition Module Transcribing Audio with Google Web Speech API/3. The SpeechRecognition library Google Web Speech API.mp460.62MB
  307. 55. Speech Recognition Module Transcribing Audio with Google Web Speech API/4. Evaluation metrics WER and CER.mp433.78MB
  308. 55. Speech Recognition Module Transcribing Audio with Google Web Speech API/5. Calculating WER and CER in Python.mp450.77MB
  309. 56. Speech Recognition Module Background Noise and Spectrograms/1. Understanding noise in audio files.mp439.34MB
  310. 56. Speech Recognition Module Background Noise and Spectrograms/2. Creating a spectrogram with Python.mp457.18MB
  311. 56. Speech Recognition Module Background Noise and Spectrograms/3. Dealing with background noise.mp485.88MB
  312. 57. Speech Recognition Module Transcribing Audio with OpenAI's Whisper/1. 9.1Whisper AI Transformer-based speech-to-text.mp470.87MB
  313. 57. Speech Recognition Module Transcribing Audio with OpenAI's Whisper/3. Transcribing multiple audio files from a directory.mp436.67MB
  314. 57. Speech Recognition Module Transcribing Audio with OpenAI's Whisper/4. Saving audio transcriptions to CSV for easy analysis.mp440.51MB
  315. 57. Speech Recognition Module Transcribing Audio with OpenAI's Whisper/5. Reversing the process AI-powered text-to-speech.mp426.21MB
  316. 58. Speech Recognition Module Final Discussion and Future Directions/1. Modern practices and applications.mp475.88MB
  317. 58. Speech Recognition Module Final Discussion and Future Directions/2. Challenges and limitations.mp439.38MB
  318. 58. Speech Recognition Module Final Discussion and Future Directions/3. The future of speech recognition with AI.mp446.56MB
  319. 59. LLM Engineering Module Introduction/1. Introduction to the Course.mp444.85MB
  320. 59. LLM Engineering Module Introduction/2. What does the course cover.mp423.38MB
  321. 59. LLM Engineering Module Introduction/3. The Interview Tool’s Specifics.mp465.6MB
  322. 60. LLM Engineering Module Planning stage/1. Hosting an LLM vs Using an API.mp443.82MB
  323. 60. LLM Engineering Module Planning stage/10. Concluding the Planning Stage.mp420.02MB
  324. 60. LLM Engineering Module Planning stage/2. Open-Source vs Closed-Source Models.mp487.13MB
  325. 60. LLM Engineering Module Planning stage/3. Tokens.mp451.98MB
  326. 60. LLM Engineering Module Planning stage/4. Pricing Hosting an LLM vs Pay-by-Token.mp441.85MB
  327. 60. LLM Engineering Module Planning stage/5. Initial Prompt Development Part 1.mp448.24MB
  328. 60. LLM Engineering Module Planning stage/6. Initial Prompt Development Part 2.mp449.75MB
  329. 60. LLM Engineering Module Planning stage/7. Database Design and Schema Development.mp435.64MB
  330. 60. LLM Engineering Module Planning stage/8. What Is an Activity Diagram.mp442.23MB
  331. 60. LLM Engineering Module Planning stage/9. Creating an Activity Diagram.mp450.69MB
  332. 61. LLM Engineering Module Crafting and Testing AI Prompts/1. The OpenAI Playground.mp467.95MB
  333. 61. LLM Engineering Module Crafting and Testing AI Prompts/2. Optimizing Temperature and Top P for Different Use Cases.mp472.37MB
  334. 61. LLM Engineering Module Crafting and Testing AI Prompts/3. Prompt Engineering for Software Development.mp460.4MB
  335. 61. LLM Engineering Module Crafting and Testing AI Prompts/4. How to Test Out a Prompt Template.mp422.28MB
  336. 62. LLM Engineering Module Getting to Know Streamlit/1. Setting up environment.mp457.59MB
  337. 62. LLM Engineering Module Getting to Know Streamlit/2. Streamlit's Pros and Cons.mp431.23MB
  338. 62. LLM Engineering Module Getting to Know Streamlit/3. Streamlit Elements Titles, Headers, and Formatting.mp414.18MB
  339. 62. LLM Engineering Module Getting to Know Streamlit/4. Streamlit Elements Text Methods.mp423.76MB
  340. 62. LLM Engineering Module Getting to Know Streamlit/5. Streamlit Elements Chat Elements.mp421.59MB
  341. 62. LLM Engineering Module Getting to Know Streamlit/6. Sessin State.mp435.43MB
  342. 63. LLM Engineering Module Developing the prototype/1. Initializing an OpenAI Client.mp422.36MB
  343. 63. LLM Engineering Module Developing the prototype/2. Implementing the Chat Functionality.mp432.19MB
  344. 63. LLM Engineering Module Developing the prototype/3. Building the Setup Page.mp451.91MB
  345. 63. LLM Engineering Module Developing the prototype/4. Enhancing Chatbot Interaction with Session State.mp448.96MB
  346. 63. LLM Engineering Module Developing the prototype/5. Refining Our Project.mp423.19MB
  347. 63. LLM Engineering Module Developing the prototype/6. Implementing Feedback Functionality Part 1.mp433.87MB
  348. 63. LLM Engineering Module Developing the prototype/7. Implementing Feedback Functionality Part 2.mp454.07MB
  349. 63. LLM Engineering Module Developing the prototype/8. Uploading Your Project in GitHub.mp439.01MB
  350. 63. LLM Engineering Module Developing the prototype/9. Deploying Your Streamlit App.mp428.02MB
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