Data Science Dojo

OCTOBER 31, 2023

The function uses the VectorStoreIndex.from_documents method to create a vector index from a set of documents, with the service context specified. It builds a query engine (queryEngine) from the vector index. mkdir -p ‘dataset’ ! It builds a query engine (queryEngine) from the vector index.

195

195

Towards AI

FEBRUARY 18, 2024

The same functionalities as for person names are used in this function, as shown in the code below, with the exception of part of speech tagging for singular and plural nouns. spaCy processing pipeline is used to accomplish this, as shown below.

Natural Language Processing 106

Natural Language Processing Python AI AI 106

Mlearning.ai

MARCH 4, 2023

In this tutorial, we will perform EDA on the S&P 500 dataset using Python. We will be using the S&P 500 dataset , which contains stock prices of the 500 largest publicly traded companies in the United States. In this tutorial, we performed EDA on the S&P 500 dataset using Python. csv') 2. pct_change().dropna(),

Exploratory Data Analysis 52

Exploratory Data Analysis Data Analysis Data Analysis EDA 52

Becoming Human

JUNE 5, 2023

topic_title_tags = doc.find_all('p', {'class':title_class}) : This line uses the find_all() method of the BeautifulSoup object to find all HTML elements ( <p> ) with the specified CSS class ( title_class ). csv', index=None) The code snippet demonstrates the main execution flow of the script.

Python 59

Python Artificial Intelligence Artificial Intelligence Data Analysis 59

Tableau

DECEMBER 23, 2020

The 2019 Global Multidimensional Poverty Index by Lali Jularbal. The Multidimensional Poverty Index (MPI) takes an in-depth look at how people experience three dimensions of poverty—Health, Education, and Living Standards—in 101 developing countries. by Praveen P Jose . See a viz that you love? Favorite this viz. .

Tableau 87

Tableau 87

Mlearning.ai

JANUARY 22, 2024

A Gentle Introduction to Time Series Analysis and Forecasting Photo by Aron Visuals on Unsplash Definition A time series is a sequence of observations indexed by time. This tuple contains the test-statistic, p-value, and critical values at different confidence levels. Here, we will use the p-value. The code is on GitHub.

Python 52

Python Machine Learning Machine Learning ML 52

Mlearning.ai

JULY 20, 2023

Formula: Adjusted R squared = 1 — ((1 — R²) * (n — 1)) / (n — p — 1), where R squared is the coefficient of determination, n is the total number of instances, and p is the number of predictors. Davies-Bouldin Index: The Davies-Bouldin index calculates the average similarity between clusters while considering their separation.

Clustering 40

Clustering Machine Learning Machine Learning Algorithm 40

Iguazio

SEPTEMBER 20, 2023

Scaling NLP Pipelines Building sophisticated NLP pipelines that operate at scale is essential for turning massive amounts of unstructured data to a searchable and indexable one. Such a pipeline ingests, prepares, classifies and indexes structured and unstructured data, handles terabytes of data, seamlessly deploys models, and leverages CI/CD.

Machine Learning 96

Machine Learning Machine Learning Database Clustering 96

Tableau

DECEMBER 23, 2020

The 2019 Global Multidimensional Poverty Index by Lali Jularbal. The Multidimensional Poverty Index (MPI) takes an in-depth look at how people experience three dimensions of poverty—Health, Education, and Living Standards—in 101 developing countries. by Praveen P Jose . See a viz that you love? Favorite this viz. .

Tableau 52

Tableau 52

DrivenData Labs

FEBRUARY 19, 2024

index [ 0 ] print ( image_id ) ax = display_image ( image_id , show_bbox = True ) 069a74eff3943d8c096bb37c7c674832 Section 2: Demo submission ¶ Now that we've had a chance to get a feel for the data, it's time to walk through the steps for creating a competition submission. to_series (). png" ). exists ] train_meta. sample ( 1 ).

Python 130

Python Algorithm Azure 130

Mlearning.ai

MARCH 4, 2023

to_csv('name.csv', header=True, index=False) Originally published at [link]. Load the data into pdf. replace(' ', 'nn').strip() apply(lambda x: len(tokenizer.encode(x))) df1 = df1[df1.n_tokens<2000] n_tokens<2000] len(df1) now split the data into 2 chunks of each 20 dfcontent = df1.iloc[:20].copy() iloc[20:40].copy()

Azure 52

Azure Machine Learning Machine Learning AI 52

Mlearning.ai

FEBRUARY 17, 2023

open a new terminal tab and type these commands in your terminal: npm install -D tailwindcss postcss autoprefixer npx tailwindcss init -p Add the paths to all of your template files in your tailwind.config.js It provides you with modular, customizable classes that can be used to quickly build responsive layouts for the web. 0 010 1.5H5.135a1.5

AI 52

AI AI ML ML 52

Towards AI

DECEMBER 20, 2023

Its support for various data types, indexing options, and complex queries positions it as a versatile solution for data management. mysql -u root -p --local_infile After entering the password successfully, you should see the below. This command ensures that you are in the correct directory for accessing MySQL’s command-line tools.

Database 99

Database SQL Python AI 99

The MLOps Blog

DECEMBER 19, 2022

The Loss function for Triplet Loss is as follows: L(a, p, n) = max(0, D(a, p) — D(a, n) + margin) where D(x, y): the distance between the learned vector representation of x and y. Creating the index. index = faiss.IndexHNSWFlat(d, M) index.hnsw.efConstruction = 40 # Setting the value for efConstruction. reorder( 100 ).build()

ML 52

ML ML Algorithm Deep Learning 52

Towards AI

FEBRUARY 18, 2024

This is a satisfactory result with a p-value close to zero. Our dataset has department numbers in records, we will pivot it to bring the weekly sales record for each department. We have also dropped other columns to avoid any confusion going forward. The 95% CI for it is 27% to 33%. 63253.19.

Python 104

Python Data Preparation Algorithm AI 104

IBM Journey to AI blog

AUGUST 22, 2023

We create large-scale foundational models based on time series data and its co-relationship with work orders, event prediction, health scores, criticality index, user manuals and other unstructured data for anomaly detection. Asset performance management.

AI 80

AI AI ML ML 80

PyImageSearch

FEBRUARY 20, 2023

__name__}") print(f"Exception => {ex}") print(f"Original Array => {jax_array}") print(f"Mutated Array => {mutated_jax_array}") >>> Original Array => [1 2 3 4 5 6 7 8 9] >>> Mutated Array => [ 1 2 -56 4 5 6 7 8 9] Another key point to note is the indexing of tensors in JAX. try: print("Indexing 1000th position of a NumPy array.")

Machine Learning 114

Machine Learning Machine Learning Deep Learning Deep Learning 114

Smart Data Collective

MARCH 14, 2022

According to the 2021 Chainalysis Global Cryptocurrency Adoption Index, the Russian Federation ranks 18th globally in adopting bitcoin and other cryptocurrencies, and the conflict between Russia and Ukraine could push cryptocurrency usage within the country to new all-time highs. following the outbreak of the Russia-Ukraine conflict.

106

106

Women in Big Data

DECEMBER 13, 2023

Dr Sonal Khosla (Speaker) holds a PhD in Computer Science with a specialization in Natural Language Processing from Symbiosis International University, India with publications in peer reviewed Indexed journals. Given any sequence of words of length m, a language model assigns a probability P(w1, …, wm) to the whole sequence.

Natural Language Processing 52

Natural Language Processing Big Data Big Data Computer Science 52

Mlearning.ai

FEBRUARY 29, 2024

Davies-Bouldin Index The Davies-Bouldin Index is intended to identify sets of clusters that are well separated and compact. The index for a set of clusters is calculated as follows: 1. The Davies-Bouldin index is the average of the R ij _max​ values across all clusters.

Clustering 52

Clustering Algorithm Data Scientist ML 52

IBM Journey to AI blog

JANUARY 10, 2023

For us, one stand-out area of opportunity presented by process data analytics capability is p rocess mining: the process of finding anomalies, patterns and correlations within large data sets to predict process outcomes. This Index proved that in almost 2000 companies, organizational health is closely linked to performance.

Data Mining 52

Data Mining Data Mining Data Mining Analytics 52

ML Review

FEBRUARY 26, 2018

AliME can accommodate phrasal expressions, intention boundary switches and logical modifications owing to the intention stack and product knowledge graph Due to the vast variety of goods, knowledge graphs are combined with semantic indexes to make identification extremely effective. 5] Mnih V, Badia A P, Mirza M, et al.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Hacker News

MARCH 25, 2024

The association between household income and mean diffusivity was mediated by neurite density (B=0.084, p=0.003) and myelination (B=0.019, p=0.009); mean diffusivity partially mediated the association between household income and cognitive performance (B=0.017, p<0.05).

163

163

Mlearning.ai

MARCH 15, 2023

' + 'n' + 'Venue: ' + venue return prompt venue_description = {} for index, row in sf_events.iterrows(): if row['venue'] not in venue_description: response = openai.Completion.create( model="text-curie-001", prompt=find_venue_type(row['venue']), temperature=0.3, x), radians(loc1.y) x), radians(loc2.y)

Database 40

Database Natural Language Processing SQL Python 40

DagsHub

AUGUST 19, 2023

The key steps to build a Q&A application like the Dagshub Documentation LLM are: Creating Embeddings for the documentation and indexing them into Vector DB like Chroma. Create embeddings for user query and retrieve the top N similar results to the query from the Vector DB. turbo-16k'}) mlflow.log_text data['input']=data['Queries'].apply(lambda

AWS 52

AWS Machine Learning Machine Learning Data Science 52

Flipboard

FEBRUARY 13, 2023

Then, we use the np.argmax() function to get the detection index with the maximum probability and the corresponding confidence value ( Lines 84 and 85 ). Building a Dataset for Triplet Loss with Keras and TensorFlow,” PyImageSearch , P. dnn.blobFromImage(cv2.resize(image, resize(image, (300, 300)), 1.0, (300, 300), (104.0, Raha, and A.

Data Pipeline 106

Data Pipeline Deep Learning Deep Learning Python 106

AWS Machine Learning Blog

MARCH 23, 2023

Decrypt results locally # extract predictions from class probabilities cl_preds = [] for prediction in predictions: logits = [PyCtxt(bytestring=p, scheme="CKKS", pyfhel=HE) for p in prediction] cl = np.argmax([HE.decryptFrac(logit)[0] for logit in logits]) c1_preds.append(cl) # compute accuracy np.mean(cl_preds == target_df.to_numpy().squeeze())

AWS 95

AWS ML ML Machine Learning 95

PyImageSearch

APRIL 24, 2023

nightly version via pip: For CUDA version 11.7: $ pip3 install numpy --pre torch --force-reinstall --extra-index-url [link] For CUDA version 11.6: $ pip3 install numpy --pre torch --force-reinstall --extra-index-url [link] However, if you don’t have CUDA 11.6 Citation Information Mangla, P. Here’s how you can install PyTorch 2.0

Deep Learning 103

Deep Learning Deep Learning Python Computer Science 103

Hacker News

MARCH 11, 2024

using Rc, or using integer indexes as ersatz pointers); it’s not just about linked lists but those are a simple well-known illustrative example. For example, the integer overflows we care most about are indexes and sizes, which fall under bounds safety. But all languages (including C++) usually have libraries and tools to address them.

Python 181

Python Algorithm SQL 181

Shreyansh Singh

MAY 28, 2023

This paper introduces Sophia, S econd- o rder Cli p ped Stoc h ast i c Optimiz a tion, a light-weight second-order optimizer that uses an inexpensive stochastic estimate of the diagonal of the Hessian as a pre-conditioner and a clipping mechanism to control the worst-case update size.

Deep Learning 52

Deep Learning Deep Learning 52

Mlearning.ai

MAY 23, 2023

What does it mean when the p-values are high and low? A p-value is the measure of the probability of having results equal to or more than the results achieved under a specific hypothesis assuming that the null hypothesis is correct. Low p-value which means values ≤ 0.05 Low p-value which means values ≤ 0.05 p-value = 0.05

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52

DrivenData Labs

DECEMBER 13, 2022

index , severity_counts. to_csv ( BENCHMARK_DATA_DIR / "image_features.csv" , index = True ) Build the model ¶ In this benchmark, we'll fit a tree-based model using the LightGBM package. choice ( [ "train" , "validation" ], size = len ( train_data ), replace = True , p = [ 0.67 , 0.33 ] ) train_data.

ML 130

ML ML Python Deep Learning 130

Mlearning.ai

JANUARY 26, 2023

STAC Index, data.europa.eu ). Upload your data to a server with a storage service able to provide HTTP range requests (e.g. S3 and Zenodo.org). Register metadata in standardised catalogue (e.g. GeoNetwork , STAC). Register your data on some public repository (e.g. Provide an interactive web-GIS interface to data (your own hosting).

AWS 98

AWS Database Clean Data Data Science 98

phData

DECEMBER 22, 2023

The common parameters for a genetic algorithm are p for the population size, g for the number of generations, and m for the mutation rate (the rate individuals in a population are mutated). Let’s unpack the algorithm in the context of Santa’s flight path problem: 1. Perform mutation on paths at a mutation rate of m.

Algorithm 52

Algorithm Python SQL Database 52

PyImageSearch

FEBRUARY 6, 2023

Training a Custom Image Classification Network for OAK-D,” PyImageSearch , P. The accuracy is printed on the terminal. astype("uint8")) plt.title(class_names[np.argmax(score[i])]) plt.axis("off") plt.savefig(config.TEST_PREDICTION_OUTPUT) On Lines 58-62 , we retrieve a batch of images from the test set, run inference on it, and apply softmax.

Deep Learning 144

Deep Learning Deep Learning Python Data Analysis 144

Shreyansh Singh

MAY 16, 2021

The proposed permutation language modeling approach is - Here Z T is the set of all possible permutations of the length- T index sequence [1, 2, 3…, T]. If both BERT and XLNet take two tokens [New, York] as the prediction task and so they have to maximize p(New York | is a city). Here again, XLNet differs from BERT.

52

52

Victor Zhou

JULY 24, 2019

Next, we’ll assign an integer index to represent each word in our vocab. Next, we’ll assign an integer index to represent each word in our vocab. The “one” in each one-hot vector will be at the word’s corresponding integer index. Let L L L be the cross-entropy loss: L = − ln ⁡ ( p c ) L = -ln(p_c) L = − ln ( p c ​ ).

Python 72

Python Machine Learning Machine Learning Natural Language Processing 72