AWS Machine Learning Blog

MAY 31, 2023

We use the following prompt: Below is SageMaker Low-code ML FAQ: ## Q: Will my data (from inference or training) be used or shared to update the base model that is offered to customers using Amazon SageMaker JumpStart? Q: Can I see the model weights and scripts of proprietary models in preview with Amazon SageMaker JumpStart?

Automation 66

Automation Python Prompt Engineer Prompt Engineering 66

Mlearning.ai

JULY 28, 2023

Follow methods 0 or 1, to create your .env Way 0: setting an environmental variable in bash using the dotenv CLI library cd /YOUR_CURRENT_WORKING_DIRECTORY Install python-dotenv[cli] from PyPI: pip install “python-dotenv[cli]” . LangChain is similar to SQL; LangChain concisely prompts the model as SQL concisely queries the database.

LLM 52

LLM Python OpenAI ML 52

PyImageSearch

DECEMBER 18, 2023

Generative AI — Addressing Concerns and Exploring Futures Quality of Models: A major topic was the quality of models in generative AI. pip install -q git+[link] !pip pip uninstall -q keras -y !pip pip uninstall -q tensorflow -y !pip pip install -q tf-nightly # needed for some data processing in keras-cv !pip

ML 67

ML Neural Network Deep Learning Machine Learning 67

Towards AI

SEPTEMBER 26, 2023

Building Simple Q&A App In this article, I will introduce you to the basics of LangChain, a framework for building applications with large… pub.towardsai.net The Models component is the backbone of Langchain. The heatmap values were presorted for better visualization. But for complicated requests, LangChain may be the way to go.

Large Language Models 52

Large Language Models OpenAI LLM Deep Learning 52

Mlearning.ai

JUNE 29, 2023

Earlier Topics: Since, We have seen centroid based algorithm for clustering like K-Means.Centroid based : K-Means, K-Means ++ , K-Medoids. & ii) Border Points:- A point “Q” is said to be border point if “Q” is not a core point. And it has the following conditions: a) “Q” has less than Min Pts in it’s “eps”(ε) radius.

Algorithm 52

Algorithm Data Mining Categorization Deep Learning 52

PyImageSearch

FEBRUARY 27, 2023

We’ll also cover the topic of randomness in JAX, including how to generate and control random numbers for use in your computations. Pure Functions Before continuing, we want to take a break and discuss a topic important to understand when using JAX, built around the idea of pure functions. This type of code should look familiar.

Neural Network 107

Neural Network Machine Learning Deep Learning Python 107

AWS Machine Learning Blog

NOVEMBER 16, 2023

0, 1, 2 Reference architecture In this post, we use Amazon SageMaker Data Wrangler to ask a uniform set of visual questions for thousands of photos in the dataset. 0 = no; 1 = yes Is the bathroom expensive? 0 = no; 1 = yes Is the kitchen expensive? 0 = no; 1 = yes Price This is the target variable to be predicted.

ML 82

ML Machine Learning Computer Vision Auto-classification 82

AWS Machine Learning Blog

AUGUST 15, 2023

Previous studies have shown how RAG can be applied to provide a Q&A solution connecting with an enterprise’s private domain knowledge. In this post, we demonstrate how to use the power of RAG in building a Q&A solution for video and audio assets on Amazon SageMaker. Each paragraph focuses on the same topic.

Chatbots 71

Chatbots Metadata LLM Generative AI 71

Flipboard

AUGUST 21, 2023

But before that, let’s quickly discuss the topics we will cover to implement people counting on OAK. objectTracker.setDetectionLabelsToTrack([0]) : Configures the object tracker to only track objects with label 0. person might be labeled as 0 , car as 1 , etc.), person might be labeled as 0 , car as 1 , etc.),

Computer Vision 88

Computer Vision Neural Network Python Deep Learning 88

Flipboard

NOVEMBER 20, 2023

tolist() sample_sentence_embedding = embedding_generator(docs[0].page_content) print_response(llm_qa_chain(question2)) We get the following answer: Q: How many awards have AWS Media Services won in 2023? Let’s see if we can improve it by providing some context. split('n')] response = 'n'.join(temp) A: I’m happy to help!

Auto-complete 128

Auto-complete LLM Machine Learning Natural Language Processing 128

Heartbeat

NOVEMBER 6, 2023

Foundation Model A foundation model is the base model that is built on top of a highly complex architecture and is trained on massive text corpora covering various topics. The corpus can be related to a single topic or cover various subjects depending on the LLM requirements. Let’s discuss a few components common to all LLM projects.

LLM 52

LLM Machine Learning Deep Learning Natural Language Processing 52

PyImageSearch

FEBRUARY 12, 2024

See the safety settings topic for details. pip install -q -U google-generativeai Line 1: Installs the google-generativeai library. waitKey(0) cv2.destroyAllWindows() waitKey(0) cv2.destroyAllWindows() GaussianBlur(image, (5, 5), 0) # Display the blurred image cv2.imshow('Blurred waitKey(0) cv2.destroyAllWindows()

Computer Vision 64

Computer Vision Python Deep Learning ChatGPT 64

PyImageSearch

FEBRUARY 19, 2024

pip install -q -U google-generativeai Line 1: Installs the google-generativeai library Step 2: Importing Essential Python Packages import textwrap import google.generativeai as genai from IPython.display import Markdown Lines 1-3: Imports three key Python packages. Ensure this aligns with the number of classes in your dataset (e.g.,

Computer Vision 60

Computer Vision ChatGPT Deep Learning Python 60

AWS Machine Learning Blog

APRIL 18, 2023

0-9]+)"}, {'Name': 'eval:loss', 'Regex': "'eval_loss': ([0-9]+.[0-9]+)"}, 0-9]+)"}, {'Name': 'eval:runtime', 'Regex': "'eval_runtime': ([0-9]+.[0-9]+)"}, 0-9]+)"}, {'Name': 'eval:samples_per_second', 'Regex': "'eval_samples_per_second': ([0-9]+.[0-9]+)"}, False , and 0, respectively.

Large Language Models 65

Large Language Models LLM NLP Deep Learning 65

PyImageSearch

MAY 1, 2023

The format of each row is class_id center_x center_y width height where fields are space-delimited, and the coordinates are normalized from 0 to 1. unzip -q hand_gesture.zip !rm For example, if four objects exist in one image, the text file would have four rows containing the class label and bounding box coordinates. Python-3.9.16

Computer Vision 107

Computer Vision Deep Learning Neural Network Python 107

PyImageSearch

DECEMBER 19, 2022

Nodes (id): == ColorCamera (0) DetectionNetwork (1) XLinkOut (2) XLinkOut (3) XLinkOut (4) Connections: 0 DetectionNetwork (1): outNetwork → XLinkOut (4): [8] in 1 DetectionNetwork (1): out → XLinkOut (3): [8] in 2 ColorCamera (0): preview → DetectionNetwork (1): [5] in 3 ColorCamera (0): preview → XLinkOut (2): [8] in Enough of theory, right? . #

Neural Network 52

Neural Network Computer Vision Deep Learning Metadata 52

PyImageSearch

MAY 15, 2023

putText(frame, config.LABELS[detection.label], (bbox[0] + 10, bbox[1] + 25), cv2.FONT_HERSHEY_TRIPLEX, putText(frame, f"{int(detection.confidence * 100)}%", (bbox[0] + 10, bbox[1] + 60), cv2.FONT_HERSHEY_TRIPLEX, putText(frame, config.LABELS[detection.label], (bbox[0] + 10, bbox[1] + 25), cv2.FONT_HERSHEY_TRIPLEX,

Computer Vision 102

Computer Vision Neural Network Metadata Deep Learning 102

AWS Machine Learning Blog

APRIL 18, 2023

0-9]+)"}, {'Name': 'eval:loss', 'Regex': "'eval_loss': ([0-9]+.[0-9]+)"}, 0-9]+)"}, {'Name': 'eval:runtime', 'Regex': "'eval_runtime': ([0-9]+.[0-9]+)"}, 0-9]+)"}, {'Name': 'eval:samples_per_second', 'Regex': "'eval_samples_per_second': ([0-9]+.[0-9]+)"}, False , and 0, respectively.

LLM 52

LLM NLP Deep Learning ML 52

Heartbeat

AUGUST 16, 2023

list( q='entertainment', type='video', videoDefinition='high', videoDuration='short', part='id', maxResults=50, pageToken=next_page_token ).execute() In this case, I divided each video into 32 frames to reduce the class imbalance. jpg') # Save the frame to disk cv2.imwrite(output_path,

Python 52

Python Computer Vision Deep Learning ML 52

Heartbeat

SEPTEMBER 12, 2023

Here are the topics we’ll cover in this article: Fine-tuning the BERT model with the Transformers library for text classification. pip install -q comet_ml transformers datasets gradio After that, let’s go ahead and initialize the platforms we will use. This is where AI platforms come in. Building a web app with the Gradio.

BERT 52

BERT Deep Learning Machine Learning ML 52

PyImageSearch

JANUARY 23, 2023

Let us assume that is 0 , so the score for the root node (purple) becomes 0. For our dummy scenario, the value is set to 0. pip install -q kaggle !mkdir We use 500 trees, with a value of 0 and a maximum depth of each tree of 5. Here, value is the Output value without the. The score for the red node becomes 225.

Computer Vision 107

Computer Vision Deep Learning Neural Network Algorithm 107

PyImageSearch

JULY 17, 2023

The pixel values fall in the range of 0 to 255. As a preprocessing step, these pixel values are normalized to fall from 0 to 1. Finally, from Lines 48-59 , the CLASS_LABELS dictionary maps class labels (integers from 0 to 9 ) to the corresponding class names. normalize=True will shift/resize the images to the range of (0, 1).

Computer Vision 98

Computer Vision Deep Learning Python Machine Learning 98

Mlearning.ai

JUNE 26, 2023

For instance, if the price per square meter in a specific area is determined as 2000 (with no initial value), the price of any house in that area can be calculated using the formula f(x) = 2000x , where x > 0. These topics will be explored in subsequent articles. [1]

Machine Learning 52

Machine Learning ML Data Analysis Python 52

AWS Machine Learning Blog

NOVEMBER 7, 2023

Large language models (LLMs) with their broad knowledge, can generate human-like text on almost any topic. Today, we are excited to unveil three generative AI demos, licensed under MIT-0 license : Amazon Kendra with foundational LLM – Utilizes the deep search capabilities of Amazon Kendra combined with the expansive knowledge of LLMs.

Large Language Models 89

Large Language Models Generative AI LLM AI 89

Pickl AI

APRIL 26, 2024

It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques. Additionally, it delves into case study questions, advanced technical topics, and scenario-based queries, highlighting the skills and knowledge required for success in data analytics roles.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Pragnakalp

JANUARY 1, 2024

This sequence is generated by starting with 0, 1, and applying the following recursive rule: the next number is the sum of the previous two numbers multiplied by 2 and then adding 1. LLaMA-2-13b-chat response: The question of what came before the Big Bang is a topic of ongoing debate and research among scientists and cosmologists.

Python 52

Python Natural Language Processing Explainability NLP 52

PyImageSearch

APRIL 3, 2023

e_x = np.exp(x - np.max(x)) return e_x / e_x.sum(axis=0) def to_planar(arr: np.ndarray, shape: tuple) -> np.ndarray: # resize the image array and modify the channel dimensions resized = cv2.resize(arr, transpose(1, 2, 0).astype(np.uint8) imshow("rgb", frame) # break out of the loop if `q` key is pressed if cv2.waitKey(1)

Neural Network 64

Neural Network Computer Vision Deep Learning Artificial Intelligence 64

John Snow Labs

MAY 25, 2023

Sentiment analysis studies the subjective information in an expression, that is, opinions, appraisals, emotions, or attitudes towards a topic, person or entity. By default, the sentiment score will be assigned labels “positive” if the score is >= 0, else “negative”. transform(data).show(truncate transform(data).show(truncate

NLP 52

NLP Machine Learning Neural Network ML 52

Snorkel AI

MARCH 16, 2023

In one case, one inspector had 0% escape (i.e. We were targeting near 0% escapes, so if we were to start off with those kind of definitions, we could never achieve our objectives. Q & A for LandingLens presentation Aarti Bagul: Amazing, thank you so much, Dillon! One of the issues is small data.

Machine Learning 52

Machine Learning ML AI AI 52

Snorkel AI

MARCH 16, 2023

In one case, one inspector had 0% escape (i.e. We were targeting near 0% escapes, so if we were to start off with those kind of definitions, we could never achieve our objectives. Q & A for LandingLens presentation Aarti Bagul: Amazing, thank you so much, Dillon! One of the issues is small data.

Machine Learning 52

Machine Learning ML AI AI 52

Sebastian Ruder

NOVEMBER 14, 2022

I will be focusing on topics related to natural language processing (NLP) and African languages as these are the domains I am most familiar with. It covers the following high-level topics: Status Quo Recent Progress Challenges and Opportunities Status Quo There are around 7,000 languages spoken around the world. Chen, Z., & Wei, F.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics AI 52