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“…You will learn to write efficient PySpark code for batch and streaming ELT jobs on Azure. …”

“…You’ll also discover the PyGame library, which is popularly used in the development of 2D games. …”

Tabla de Contenidos: “…Getting started -- The program -- The header -- Implementing Google's translation service -- Google Translate from a linguist's perspective -- Playing with the tool -- Linguistic assessment of Google Translate -- AI as a new frontier -- Lexical field and polysemy -- Exploring the frontier - customizing Google Translate with a Python program -- k-nearest neighbor algorithm -- Implementing the KNN algorithm -- The knn_polysemy.py program -- Implementing the KNN function in Google_Translate_Customized.py -- Conclusions on the Google Translate customized experiment -- The disruptive revolutionary loop -- Summary -- Questions -- Further reading -- Chapter 7: Optimizing Blockchains with Naive Bayes -- Part I - the background to blockchain technology -- Mining bitcoins -- Using cryptocurrency -- PART II - using blockchains to share information in a supply chain -- Using blockchains in the supply chain network -- Creating a block -- Exploring the blocks -- Part III - optimizing a supply chain with naive Bayes in a blockchain process -- A naive Bayes example -- The blockchain anticipation novelty -- The goal - optimizing storage levels using blockchain data -- Implementation of naive Bayes in Python -- Gaussian naive Bayes -- Summary -- Questions -- Further reading -- Chapter 8: Solving the XOR Problem with a Feedforward Neural Network -- The original perceptron could not solve the XOR function -- XOR and linearly separable models -- Linearly separable models -- The XOR limit of a linear model, such as the original perceptron -- Building an FNN from scratch -- Step 1 - defining an FNN -- Step 2 - an example of how two children can solve the XOR problem every day -- Implementing a vintage XOR solution in Python with an FNN and backpropagation -- A simplified version of a cost function and gradient descent -- Linear separability was achieved…”

Tabla de Contenidos: “…Improved password handling with hybrid attributesAPI authentication; Authentication protocols; Getting users; Creating new users; API testing; Interlude - Werkzeug middlewares; Back to Shutterbug - uploading photos; Testing the photo uploads; Fetching the user's photos; Summary; Chapter 6: Hublot - Flask CLI Tools; Starting off; The manage.py file; The built-in default commands; The Flask-Script commands across Blueprints; Submanagers; The required and optional arguments; Flask extensions - the basics; When should an extension be used?…”

Tabla de Contenidos: “…IntroductionFinding a protein in multiple databases; Introducing Bio.PDB; Extracting more information from a PDB file; Computing molecular distances on a PDB file; Performing geometric operations; Implementing a basic PDB parser; Animating with PyMol; Parsing mmCIF files using Biopython; Chapter 8: Other Topics in Bioinformatics; Introduction; Accessing the Global Biodiversity Information Facility; Geo-referencing GBIF datasets; Accessing molecular-interaction databases with PSIQUIC; Plotting protein interactions with Cytoscape the hard way; Chapter 9: Python for Big Genomics Datasets…”

Tabla de Contenidos: “…Clients; Using Redis from the Command Line; Problem; Solution; Discussion; Using Redis from Python with redis-py; Problem; Solution; Discussion; Using Redis from Ruby with redis-rb; Problem; Solution; Discussion; Using Redis with Ruby on Rails; Problem; Solution; Discussion; Adding Redis functionality to ActiveRecord models; Chapter 3. …”

Tabla de Contenidos: “…Adding a parameter to a decorator -- Implementing more complex decorators -- Complex design considerations -- Summary -- Chapter 12: The Multiprocessing and Threading Modules -- Functional programming and concurrency -- What concurrency really means -- The boundary conditions -- Sharing resources with process or threads -- Where benefits will accrue -- Using multiprocessing pools and tasks -- Processing many large files -- Parsing log files - gathering the rows -- Parsing log lines into namedtuples -- Parsing additional fields of an Access object -- Filtering the access details -- Analyzing the access details -- The complete analysis process -- Using a multiprocessing pool for concurrent processing -- Using apply() to make a single request -- Using the map_async(), starmap_async(), and apply_async() functions -- More complex multiprocessing architectures -- Using the concurrent.futures module -- Using concurrent.futures thread pools -- Using the threading and queue modules -- Designing concurrent processing -- Summary -- Chapter 13: Conditional Expressions and the Operator Module -- Evaluating conditional expressions -- Exploiting non-strict dictionary rules -- Filtering true conditional expressions -- Finding a matching pattern -- Using the operator module instead of lambdas -- Getting named attributes when using higher-order functions -- Starmapping with operators -- Reducing with operator module functions -- Summary -- Chapter 14: The PyMonad Library -- Downloading and installing -- Functional composition and currying -- Using curried higher-order functions -- Currying the hard way -- Functional composition and the PyMonad * operator -- Functors and applicative functors -- Using the lazy List() functor -- Monad bind() function and the &gt -- &gt -- operator -- Implementing simulation with monads -- Additional PyMonad features -- Summary…”

Tabla de Contenidos: “…Additional reading -- Chapter 6: Using Stable Diffusion Models -- Technical requirements -- Loading the Diffusers model -- Loading model checkpoints from safetensors and ckpt files -- Using ckpt and safetensors files with Diffusers -- Turning off the model safety checker -- Converting the checkpoint model file to the Diffusers format -- Using Stable Diffusion XL -- Summary -- References -- Part 2 - Improving Diffusers with Custom Features -- Chapter 7: Optimizing Performance and VRAM Usage -- Setting the baseline -- Optimization solution 1 - using the float16 or bfloat16 data type -- Optimization solution 2 - enabling VAE tiling -- Optimization solution 3 - enabling Xformers or using PyTorch 2.0 -- Optimization solution 4 - enabling sequential CPU offload -- Optimization solution 5 - enabling model CPU offload -- Optimization solution 6 - Token Merging (ToMe) -- Summary -- References -- Chapter 8: Using Community-Shared LoRAs -- Technical requirements -- How does LoRA work? …”

Texto completo en Odilo

Texto completo en Odilo

Texto completo en Odilo

Texto completo en Odilo

Texto completo en Odilo

Texto completo en Odilo

Texto completo en Odilo

Texto completo en Odilo

Texto completo en Odilo