Hire Data Scientists
Hire LeewayHertz’s expert data scientists to efficiently source, manage, and analyze large amounts of unstructured data. Our data scientists have extensive experience analyzing, visualizing and preprocessing complex data sets using manual techniques and automated tools like Pandas and NumPy to ensure they are ready for seamless training of your AI models.
Software Products Delivered
Total Years of Experience
Services Offered by Our Data Scientists
Hire data scientists from LeewayHertz to tap into the potential of data and drive business growth.
Data Gathering and Preprocessing
Our data scientists collect structured and unstructured data using web scraping and API integration and prepare them using techniques like feature engineering and data normalization to ensure the data is ready for model training.
By labeling and categorizing data using manual techniques and automated tools like Hugging Face’s datasets library, our data scientists enable machine learning algorithms to recognize patterns and make accurate predictions.
Algorithm Selection and Hyperparameter Tuning
Our data scientists leverage techniques like EDA, experimentation, and hypothesis testing to select the ideal ML algorithm for your project. They also use methods like Grid search and Bayesian optimization for hyperparameter tuning to ensure there are no inefficiencies in the model being developed.
Model Training and Validation
We use numerous ML techniques like supervised and unsupervised learning and reinforcement learning to train the model and validate it for accuracy using techniques like cross-validation, confusion matrix and ROC curve.
Once deployed, our data scientists use evaluation metrics like precision, accuracy, recall and F1 score to resolve any anomalies in the model and analyze its performance to identify underperforming segments and address any issues in them.
Our data scientists can assess your business shortcomings, analyze your data to uncover valuable insights and develop a comprehensive strategy to help you harness the full potential of your data and make well-informed, data-driven decisions for business growth.
Methods Used by Our Data Scientists to Extract Insights From Data
Machine Learning Algorithms
Our data scientists use multiple ML algorithms, like decision trees, linear regression, logistic regression, random forests, support vector machines, and KNN for classification, regression, clustering and dimensionality reduction to build AI models.
We utilize numerous deep learning algorithms and techniques like neural networks, CNNs, RNNs and autoencoders to derive valuable insights from datasets and build accurate AI models for diverse use cases.
Our data scientists select and curate labeled data for training AI models. They choose the appropriate model architecture, define the loss function and optimization algorithm and tune the model’s hyperparameters for optimal performance.
Our data scientists discover patterns and relationships in unlabeled data by choosing appropriate algorithms. They also carefully assess and interpret the unsupervised learning algorithms to draw meaningful conclusions.
We select a pre-trained model that has been trained for a task similar to the one at hand. Our data scientists design and curate the dataset for fine-tuning the model and tuning the model’s hyperparameters for optimal performance.
We utilize developer resources and advanced tools like Markov Decision Processes to employ reinforcement learning techniques, which help us train agents to perform tasks to maximize rewards based on environmental feedback.
Our data scientists utilize multiple NLP toolkits such as NLTK and SpaCy and NLP techniques like tokenization, stemming, and lemmatization to identify the root words in text data and simplify the data by breaking it down into smaller components.
We leverage computer vision to interpret and analyze digital images and videos using numerous tools and techniques, such as feature extraction, image processing techniques, OpenCV, and TensorFlow.
AI Models We Have Expertise in
A set of OpenAI models capable of performing natural language processing tasks such as text generation, summarization, translation and question answering.
A set of OpenAI models, including the highly capable and cost-effective Gpt-3.5-turbo, that improve on GPT-3 and can generate text or code.
A set of OpenAI models that can solve complex problems with high accuracy, thanks to its advanced reasoning capabilities and broader general knowledge.
DALL·E by OpenAI generates realistic images and artwork based on text prompts. It can produce images of a specified size, modify pre-existing images and generate variations of user-provided images.
Whisper is a general-purpose speech recognition OpenAI model that can perform language identification, speech translation and multilingual speech recognition.
OpenAI's Embeddings are numerical representations of linguistic units like words and phrases that capture the semantic meaning and relationships between them.
Moderation models are machine learning OpenAI models designed to assist in content moderation tasks, such as identifying and removing inappropriate or harmful content from online platforms.
Google's Bard, powered by LaMDA, is a text-to-text generative AI chatbot designed to generate human-like responses to natural language prompts, making it capable of engaging in conversations with humans.
Tech Stack Our Data Scientists Utilize
Integration and Deployment Tools
Data preprocessing tools
Data visualization tools
Our Artificial Intelligence Portfolio
Big Brands Trust Us
Our Engagement Models
Dedicated Development Team
Our blockchain developers are hands-on the cognitive technologies to deliver high-quality services and solutions to clients.
Our team extension model is intended to help clients who want to extend their team with the right expertise required for their project.
Our project-based model and software development specialists are there for customer collaboration and specific client project engagement.
Get Started Today
1. Contact Us
Fill out the contact form protected by NDA, book a calendar and schedule a Zoom Meeting with our experts.
2. Get a Consultation
Get on a call with our team to know the feasibility of your project idea.
3. Get a Cost Estimate
Based on the project requirements, we share a project proposal with budget and timeline estimates.
4. Project Kickoff
Once the project is signed, we bring together a team from a range of disciplines to kick start your project.
Start a conversation by filling the form
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What services do LeewayHertz’s data scientists offer?
Our data scientists offer various services, including data gathering and preprocessing, data annotation, algorithm selection and hyperparameter tuning, model training and validation, model evaluation and consultancy services.
What benefits do I reap when I hire data scientists from LeewayHertz?
Our data scientists have extensive experience analyzing, visualizing, and preprocessing complex data sets using manual techniques and automated tools, ensuring that the data is ready for seamless training of your AI models.
What types of businesses can benefit from the services offered by LeewayHertz’s data scientists?
Our services are ideal for any business that wants to leverage the power of data to drive better decision-making and improve workflow optimization. Our clients span a variety of industries, including healthcare, finance and e-commerce.
What kind of data can your team work with?
Our data scientists have experience working with structured and unstructured data from a variety of sources, including spreadsheets, APIs, and even raw web data. We can handle data available in a wide range of formats, including text, images, video, and audio.
How do you determine the right ML algorithm for a given project?
Our data scientists will work closely with you to understand your business needs and goals and the specifics of your data. Based on this information, we can recommend an appropriate ML algorithm or a combination of different algorithms to yield the best results for your project.
Data annotation is adding labels or tags to a training dataset to provide context and meaning to the data.
Parameter-efficient Fine-tuning (PEFT) is a technique used in Natural Language Processing (NLP) to improve the performance of pre-trained language models on specific downstream tasks.
Language models are the backbone of natural language processing (NLP) and have changed how we interact with language and technology.