Best AI tools for< mergers and acquisitions analyst >

Eilla is an AI platform that automates mundane tasks and supports complex decision-making in the M&A, VC, and PE deal workflow. It mirrors the highest quality industry professionals to provide accurate and efficient assistance.

Slideworks is a website that provides high-end PowerPoint templates and toolkits created by ex-McKinsey and BCG consultants. The templates are designed to help users create world-class strategy presentations, business cases, market analyses, and more. Slideworks also offers a consulting service to help users with their strategy work. Slideworks' templates are fully customizable and easy to use. They come with a complete storyline, best-practice slide layouts, helpful checklists, and step-by-step guides. Users can also access future updates to the templates. Slideworks is trusted by over 4,500 customers worldwide, including some of the world's leading companies. The company's templates have been used to create presentations for a variety of purposes, including: * Strategy presentations * Business cases * Market analyses * Consulting proposals * Due diligence reports * Mergers and acquisitions presentations * Digital transformation presentations * Product strategy presentations * Go-to-market strategy presentations * Operational excellence presentations

Inkdrop is a cloud-based tool that helps visualize and manage Terraform code. It provides an interactive demo that allows users to see how their Terraform code will be deployed, and it also integrates with GitHub and Atlantis to automatically update documentation. Inkdrop's key features include: * Visualize Terraform code and deployments * Filter resources by tags, type, and state * Seamless integration with GitHub and Atlantis Inkdrop's advantages include: * Speeds up onboarding and understanding of Terraform code * Helps identify infrastructure that is relevant to users * Automates documentation updates Inkdrop's disadvantages include: * May require a learning curve for new users * Can be slow to load large Terraform codebases * Lacks some advanced features found in other Terraform visualization tools

Yet Another Mail Merge (YAMM) is a free tool that allows you to send personalized emails from Gmail using Google Sheets. With YAMM, you can easily create and send mail merge campaigns directly from Gmail, without having to use any complicated software or coding. YAMM is a great tool for businesses and individuals who want to send personalized emails to a large number of people, such as customers, leads, or subscribers.

HiPDF is a free online PDF solution that offers a wide range of tools for editing, converting, compressing, and organizing PDFs. It also includes AI-powered tools such as Chat with PDF and AI Detector. With HiPDF, you can easily edit PDFs in your browser, convert PDFs to and from other formats, compress PDFs to reduce their size, and merge, split, and extract images from PDFs. You can also protect your PDFs with passwords and redact sensitive information. HiPDF is a convenient and easy-to-use tool that can help you with all your PDF needs.

**Wondershare: The Leading Software Company for Creativity, Productivity, and Utility** **Video Editing** - Filmora: A powerful and easy-to-use video editor for beginners and professionals alike. - Filmstock: A vast library of royalty-free stock footage, effects, and music. **PDF Solutions** - PDFelement: A comprehensive PDF editor and converter. - PDFelement for iOS: A mobile PDF editor for iOS devices. **Document Cloud** - Document Cloud: A cloud-based platform for managing and sharing documents. **Data Recovery** - Recoverit: A powerful data recovery software for recovering lost files from various devices. **Mobile Transfer** - MobileTrans: A tool for transferring data between mobile devices. - MobileTrans for WhatsApp: A tool for transferring WhatsApp data between Android and iPhone. **Other Tools** - Mutsapper: A tool for recovering WhatsApp messages from Android and iPhone. - PDF Converter Pro: A powerful PDF converter for converting PDF files to various formats. - PDF Editor Pro: A professional PDF editor for creating, editing, and converting PDF files. - PDF Merger: A tool for merging multiple PDF files into a single file. **Why Choose Wondershare?** - Over 20 years of experience in the software industry. - A team of over 1,000 engineers and designers. - Products that are used by over 150 million people worldwide. - A commitment to providing innovative and user-friendly software. **Featured Products** - Filmora: A powerful and easy-to-use video editor for beginners and professionals alike. - PDFelement: A comprehensive PDF editor and converter. - Recoverit: A powerful data recovery software for recovering lost files from various devices. - MobileTrans: A tool for transferring data between mobile devices. **Advantages** - User-friendly interface - Powerful features - Affordable pricing - Excellent customer support **Disadvantages** - Some features may require a subscription - Not all features are available on all platforms - Some users may find the interface to be too cluttered **FAQs** - Q: What is Wondershare? A: Wondershare is a leading software company that provides a wide range of software products for creativity, productivity, and utility. - Q: What are some of Wondershare's most popular products? A: Some of Wondershare's most popular products include Filmora, PDFelement, Recoverit, and MobileTrans. - Q: How much do Wondershare products cost? A: Wondershare products range in price from free to several hundred dollars. The price of a product will vary depending on the features and functionality that it offers. - Q: Where can I buy Wondershare products? A: Wondershare products can be purchased from the Wondershare website or from authorized resellers. - Q: What is Wondershare's customer support like? A: Wondershare offers excellent customer support via email, phone, and live chat.

The AI Toolkit by Ostris is a collection of tools for machine learning, specifically designed for image generation, LoRA (latent representations of attributes) extraction and manipulation, and model training. It provides a user-friendly interface and extensive documentation to make it accessible to both developers and non-developers. The toolkit is actively under development, with new features and improvements being added regularly. Some of the key features of the AI Toolkit include: - Batch Image Generation: Allows users to generate a batch of images based on prompts or text files, using a configuration file to specify the desired settings. - LoRA (lierla), LoCON (LyCORIS) Extractor: Facilitates the extraction of LoRA and LoCON representations from pre-trained models, enabling users to modify and manipulate these representations for various purposes. - LoRA Rescale: Provides a tool to rescale LoRA weights, allowing users to adjust the influence of specific attributes in the generated images. - LoRA Slider Trainer: Enables the training of LoRA sliders, which can be used to control and adjust specific attributes in the generated images, offering a powerful tool for fine-tuning and customization. - Extensions: Supports the creation and sharing of custom extensions, allowing users to extend the functionality of the toolkit with their own tools and scripts. - VAE (Variational Auto Encoder) Trainer: Facilitates the training of VAEs for image generation, providing users with a tool to explore and improve the quality of generated images. The AI Toolkit is a valuable resource for anyone interested in exploring and utilizing machine learning for image generation and manipulation. Its user-friendly interface, extensive documentation, and active development make it an accessible and powerful tool for both beginners and experienced users.

This repository contains a minimal, clean code implementation of the Byte Pair Encoding (BPE) algorithm, commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings. This algorithm was popularized for LLMs by the GPT-2 paper and the associated GPT-2 code release from OpenAI. Sennrich et al. 2015 is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers. There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows: 1. minbpe/base.py: Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from. 2. minbpe/basic.py: Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text. 3. minbpe/regex.py: Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any. 4. minbpe/gpt4.py: Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the tiktoken library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations. Finally, the script train.py trains the two major tokenizers on the input text tests/taylorswift.txt (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook. All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

VedAstro is an open-source Vedic astrology tool that provides accurate astrological predictions and data. It offers a user-friendly website, a chat API, an open API, a JavaScript SDK, a Swiss Ephemeris API, and a machine learning table generator. VedAstro is free to use and is constantly being updated with new features and improvements.

LLM-Blender is a framework for ensembling large language models (LLMs) to achieve superior performance. It consists of two modules: PairRanker and GenFuser. PairRanker uses pairwise comparisons to distinguish between candidate outputs, while GenFuser merges the top-ranked candidates to create an improved output. LLM-Blender has been shown to significantly surpass the best LLMs and baseline ensembling methods across various metrics on the MixInstruct benchmark dataset.

Mergekit is a toolkit for merging pre-trained language models. It uses an out-of-core approach to perform unreasonably elaborate merges in resource-constrained situations. Merges can be run entirely on CPU or accelerated with as little as 8 GB of VRAM. Many merging algorithms are supported, with more coming as they catch my attention.

Tiny-Predictive-Text is a demonstration of predictive text without an LLM, using permy.link. It provides a detailed description of the tool, including its features, benefits, and how to use it. The tool is suitable for a variety of jobs, including content writers, editors, and researchers. It can be used to perform a variety of tasks, such as generating text, completing sentences, and correcting errors.

Stable Diffusion web UI is a web interface for Stable Diffusion, implemented using Gradio library. It provides a user-friendly interface to access the powerful image generation capabilities of Stable Diffusion. With Stable Diffusion web UI, users can easily generate images from text prompts, edit and refine images using inpainting and outpainting, and explore different artistic styles and techniques. The web UI also includes a range of advanced features such as textual inversion, hypernetworks, and embeddings, allowing users to customize and fine-tune the image generation process. Whether you're an artist, designer, or simply curious about the possibilities of AI-generated art, Stable Diffusion web UI is a valuable tool that empowers you to create stunning and unique images.

The 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.

DeFiChain is a blockchain platform dedicated to enabling decentralized finance with Bitcoin-grade security, strength, and immutability. It offers fast, intelligent, and transparent financial services accessible to everyone. DeFiChain has made significant modifications from Bitcoin Core, including moving to Proof-of-Stake, introducing a masternode model, supporting a community fund, anchoring to the Bitcoin blockchain, and enhancing decentralized financial transaction and opcode support. The platform is under active development with regular releases and contributions are welcomed.

llama.cpp is a C++ implementation of LLaMA, a large language model from Meta. It provides a command-line interface for inference and can be used for a variety of tasks, including text generation, translation, and question answering. llama.cpp is highly optimized for performance and can be run on a variety of hardware, including CPUs, GPUs, and TPUs.

EdgeChains is an open-source chain-of-thought engineering framework tailored for Large Language Models (LLMs)- like OpenAI GPT, LLama2, Falcon, etc. - With a focus on enterprise-grade deployability and scalability. EdgeChains is specifically designed to **orchestrate** such applications. At EdgeChains, we take a unique approach to Generative AI - we think Generative AI is a deployment and configuration management challenge rather than a UI and library design pattern challenge. We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure.

llm-finetuning is a repository that provides a serverless twist to the popular axolotl fine-tuning library using Modal's serverless infrastructure. It allows users to quickly fine-tune any LLM model with state-of-the-art optimizations like Deepspeed ZeRO, LoRA adapters, Flash attention, and Gradient checkpointing. The repository simplifies the fine-tuning process by not exposing all CLI arguments, instead allowing users to specify options in a config file. It supports efficient training and scaling across multiple GPUs, making it suitable for production-ready fine-tuning jobs.

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: * **Long-Context LLM** : Activation Beacon * **Fine-tuning of LM** : LM-Cocktail * **Embedding Model** : Visualized-BGE, BGE-M3, LLM Embedder, BGE Embedding * **Reranker Model** : llm rerankers, BGE Reranker * **Benchmark** : C-MTEB

Guides strategic business growth through successful mergers and acquisitions.

Facilitates successful corporate mergers and acquisitions to drive growth.

Specialist in corporate finance, offering strategic insights and best practices.

Use me to help you decide what type of business to acquire. Let's go!

Automatically prompts for and merges spreadsheets.

Your smart Web3 Navigator, merges AI with Web3. It offers AI-curated news, a vast crypto knowledge base, intelligent market analysis, and a community forum.

Expert in PDF tasks and tool advice.

Expert in Indian competition law, providing insights and guidance.

Merges photos into Powerpuff Girls team scenes.