Pandasemplois

...et des scripts Python ou R pour automatiser les extractions ; • élaborez des visualisations interactives dans Power BI ou Tableau afin de suivre nos indicateurs clés ; • recommandez des actions à partir des tendances détectées. Je fournis l’accès aux bases, la documentation technique et un canal Slack dédié. De votre côté, j’attends : – une expérience avérée en analyse de données (Python / Pandas, SQL, outils de BI) ; – la capacité à livrer des synthèses courtes et précises chaque semaine ; – un engagement régulier, 15 à 20 heures réparties comme vous le souhaitez. Si vous aimez explore...

...(rendement instantané, performance ratio, courbes I-V, pertes thermiques), puis d’analyser ces valeurs pour comprendre où se cachent les gains possibles. La démarche attendue commence par la structuration et le nettoyage du jeu de données, se poursuit par le calcul des métriques et l’exploration visuelle des tendances, et se conclut par des recommandations claires pour améliorer l’efficacité. Python (pandas, NumPy, Matplotlib), MATLAB, PVsyst ou NREL SAM conviennent tous à condition que chaque étape soit reproductible et dûment commentée : je dois pouvoir relancer votre script et obtenir les mêmes graphiques. Deliverables • Rapport analytique d’environ 10–15 pa...

...simple : automatiser le remplissage de cette image à partir des données Excel pour obtenir, en un clic, un fichier PNG/JPG prêt à être partagé. Concrètement, le script devra : • lire et structurer les données depuis l’Excel ; • placer chaque information dans l’emplacement correspondant de l’image modèle ; • générer le rendu final et l’enregistrer. J’apprécierais une solution Python (pandas, Pillow, OpenCV ou équivalent), mais je reste ouvert à toute approche fiable. Fournissez-moi : 1. le code entièrement commenté ; 2. un court guide d’exécution pour que je puisse modifier le tableau ou changer l&rs...

...création ou l’optimisation d’un modèle de classification sous Python, tout en menant l’analyse exploratoire nécessaire pour vous livrer des insights clairs. Vos jeux de données numériques, textuels et même vos images seront traités dans un pipeline cohérent : nettoyage, préparation, sélection de variables, entraînement, évaluation puis export du modèle prêt à être déployé. J’utilise couramment pandas, scikit-learn, TensorFlow/Keras et Jupyter ; je peux également intégrer votre stack existante si besoin. Livrables sous 24 h : • Notebook ou script Python entièrement commenté • Rapport concis sur ...

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...m’aider quelques heures par semaine à transformer nos chiffres en décisions concrètes. Votre rôle • Extraire et consolider les données de nos sources internes (bases SQL, exports CRM, feuilles Excel). • Nettoyer et structurer les jeux de données afin de garantir leur fiabilité. • Produire des analyses descriptives et des tableaux de bord clairs dans Power BI, Tableau ou un notebook Python/Pandas. • Mettre en lumière les tendances clés et rédiger un court résumé d’insights à chaque livraison. Ce que j’attends – 10 à 15 h de travail récurrent par semaine, horaires flexibles. – Maîtrise démontré...

...(intégration manuelle et automatisée). ⸻ Livrables attendus 1. Programme Python complet et fonctionnel. 2. Code source documenté. 3. Fichiers de données structurés et correctement saisis. 4. Mode d’emploi simplifié. 5. Session de formation à distance (1 heure) pour la prise en main. ⸻ Compétences requises • Maîtrise du langage Python (gestion de données, automatisation, interfaces). • Connaissance de pandas, tkinter, openpyxl, reportlab ou équivalents. • Bon niveau en structuration et nettoyage de données. • Fiabilité, réactivité et respect des délais. ⸻ Détails contractuels • Durée totale de la mission : 1 mois. • ...

Je mets à disposition un jeu complet de ventes immobilières passées et souha...capable d’estimer les prix futurs à partir de ces mêmes variables ; • comparer les résultats entre quartiers, types de biens ou périodes afin de dégager les écarts significatifs. Le format attendu est un rapport PDF auto-portant, rédigé en français, intégrant méthodologie, visualisations (charts, heatmaps, cartes, etc.), interprétation et recommandations. Vous êtes libre d’utiliser Python (pandas, scikit-learn, seaborn), R, Power BI ou tout autre outil tant que les sources et scripts sont fournis en annexe pour réplication. Je réponds rapidement à tout...

Recherche développeur Python (urgent – deadlineJEUDi soir) Je cherche quelqu’un pour m’aider à finaliser rapidement un projet de stage. Le projet consiste à développer un outil d’analyse de données (Python) avec i...cherche quelqu’un pour m’aider à finaliser rapidement un projet de stage. Le projet consiste à développer un outil d’analyse de données (Python) avec interface et génération de rapport. Les données proviennent de fichiers Excel et de fichiers de mesure (MDF). L’outil doit comparer les données, détecter des scénarios prédéfinis, et générer un rapport clair (HTML). Compétences souhaité...

...données pour le stockage des données financières et des allocations. API Financial Modeling Prep : API utilisée pour récupérer les données financières (prix des actions, capitalisation, etc.). SQLAlchemy / MySQL Connector : Bibliothèques utilisées pour interagir avec la base de données MySQL. TQDM : Bibliothèque de gestion de la barre de progression pour suivre l'avancement du traitement des données. Pandas / Numpy : Bibliothèques utilisées pour le traitement et la gestion des données financières sous forme de DataFrames. Demandes pour le développeur : Finalisation des scripts : Les scripts doivent être finalisés pour assurer la gestion r...

...Pour l’analyse de données et les prédictions statistiques. Compétences Requises Maîtrise de TensorFlow ou équivalent (par exemple, PyTorch) Maîtrise d’OpenCV ou équivalent (par exemple, SimpleCV) Maîtrise de PyTorch ou équivalent (par exemple, TensorFlow) Maîtrise de Keras ou équivalent (par exemple, PyTorch avec une API de haut niveau) Maîtrise de Scikit-learn ou équivalent (par exemple, Pandas pour l’analyse de données) Étapes de Développement Conception de l’Interface Utilisateur : Créer une interface web intuitive et responsive. Utiliser des frameworks comme React.js ou Vue.js pour le front-end. Développement du Backend : Ut...

...Visualizations 1. **Absence Rate Graphs** - Stacked bars to compare absences by class and gender. 2. **Academic Performance Curves** - Line graphs showing the evolution of average scores by subject over time. 3. **Dashboards** - Interactive dashboards with filters to visualize specific statistics for a class, student, or period. ## Example Code for Simple Analysis in Python ```python import pandas as pd import as plt from sklearn.linear_model import LinearRegression # Load data data = pd.read_csv('') # Calculate average scores by subject mean_scores = ('subject')['score'].mean() # Visualize average scores by subject (kind='bar') ('Average Scores by Subject') ('Subject') ('Average Score') ()

Je m’appelle Said et je cherche un formateur de programmation français .pour me réaliser une formation, serait diffusée sur YouTube juste votre écran et votre voix je veux une formation...fondamentaux de la programmation dans Python -prise en main et installations -opérations basiques en python -variables -chaînes de caractères -fonction input -les indices -les booléens et opérateurs logiques -opérateurs de comparaison -le branchement conditionnel if -boucles for et while -les listes -les dictionnaires -les fonctions Phase 2 : Python pour la Data Science -dataframe -Jupyter notebook -pandas -Matplotlib -Scikit-learn -Autres librairies très importantes -Réalisation de projets. 4 projets Po...

Je m’appelle Said et je cherche un formateur de programmation .pour me réaliser une formation, serait diffusée sur YouTube juste votre écran et votre voix je veux une formation bien orga...fondamentaux de la programmation dans Python -prise en main et installations -opérations basiques en python -variables -chaînes de caractères -fonction input -les indices -les booléens et opérateurs logiques -opérateurs de comparaison -le branchement conditionnel if -boucles for et while -les listes -les dictionnaires -les fonctions Phase 2 : Python pour la Data Science -dataframe -Jupyter notebook -pandas -Matplotlib -Scikit-learn -Autres librairies très importantes -Réalisation de projets. 4 projets Pour le t...

...reliably scrapes the data I need. The next step is to layer in proper analytics and present the results through a cleaner, mobile–friendly frontend while leaving the core scraper intact. Python scope • Extend the existing code so the scraped dataset feeds directly into statistical analysis, mathematical modelling, and quick data-visualisation routines. • Prefer familiar libraries such as Pandas, NumPy/SciPy, Matplotlib or Plotly, but I’m open to alternatives if they suit the task better. • Keep the workflow end-to-end: once the scraper finishes, the calculations should run automatically and expose structured results ready for the UI. Frontend scope • Refresh the HTML/CSS (vanilla or lightweight framework) to give the dashboard a modern,...

...clearly-structured package) that scrapes the target sites, parses the useful fields with BeautifulSoup, cleans and reshapes the data in Pandas, and spits out tidy CSV or JSON files. 2. Automated file management—old files archived, new ones stamped and stored in the correct directory automatically. 3. Clear, commented code plus a brief README so future tweaks take minutes instead of hours. I’ll provide full site lists, sample output, and the current scripts once we start. Run-time speed matters less than reliability and maintainability, so favour readable logic over micro-optimisations. As long as it’s standard Python 3 and uses well-supported libraries (Requests, BeautifulSoup, Pandas, maybe pathlib or shutil for file handling), I’m happy. I...

I’m looking for focused help with data consulting—specifically ...I have raw information in hand but need an experienced mind to walk me through the best way to clean, explore, and interpret it so that I can make confident business decisions afterward. Here is what I have in mind: • Quick review of the dataset’s structure and quality • A live or recorded walkthrough of recommended analytical steps (tool-agnostic, though I’m comfortable with Excel, Python-pandas, or Power BI if you’d like to demonstrate) • A concise summary of key findings and next-step suggestions I can action immediately Please let me know your approach, typical turnaround for an initial consultation, and any examples of similar work you’ve guided. I&rsquo...

...Data Extraction (Python/Excel) – Ready for Quick Turnaround ​Hi there, ​I am a Computer Science Engineer with strong expertise in Python and Data Processing, making me an ideal fit for your PDF data extraction project. I understand you need financial data accurately extracted from various invoices into a clean Excel format. ​Why choose me? ​Automation for Accuracy: I can use Python libraries (like Pandas and PyPDF2/Camelot) to ensure 100% accuracy and handle multi-page invoices efficiently. ​Filtering Logic: I will implement a custom script to automatically filter out non-financial pages, ensuring only relevant data reaches the final sheet. ​Quick Turnaround: I understand you need this done fast. I can start immediately and deliver a standardized, error-free Excel workbook....

I need a freelancer who can handle the full cycle of financial analysis for my Guesty account. The first ...dashboard that I can access in real time. Once the data is flowing, I want meaningful financial analysis built on top—profitability, liquidity, and efficiency ratios are the primary focus, but I’m open to additional KPIs you believe will help me steer the business more effectively. You should be comfortable with API integration, data cleaning, and whichever analytics stack you prefer (Python + Pandas, Power BI, Tableau, etc.) as long as the end result is a clear, drill-down view of performance. Please outline your approach for connecting to the Guesty API, the tools you’ll use for analysis, and how you plan to present the findings so I can make faster, ...

...Build a Python notebook that loads the three models from Hugging Face (PyTorch backend), pipes the Arabic prompts through Garak, captures logits and full responses, and writes everything to tidy CSV files. • Include bilingual testing so the notebook can toggle between the original English prompts and their Arabic counterparts, allowing side-by-side success-rate comparison. • Produce a concise pandas analysis section that calculates and visualises attack success percentages per model and per language. • Document every step—from model acquisition commands to translation strategy and evaluation metrics—in markdown cells so the methodology is fully reproducible. Acceptance criteria • Notebook runs end-to-end on a fresh environment (tested wi...

...and surface clear, actionable trends. The sole objective is to analyze historical data—specifically inventory data—so our team can understand how stock levels have moved over time and where the pressure points sit. Here’s what I have: several years of SKU-level records housed in a SQL database, plus a few CSV extracts. I need you to pull and clean the data, run robust trend analysis in Python (Pandas, NumPy, preferably some Matplotlib or Seaborn visuals), and package the insights so they are easy for our planners to act on. Time-series forecasting or demand planning frameworks aren’t required right now, but please structure the code so we could layer those in later if needed. Deliverables: • Well-documented Python notebook or script that connects to...

I need a seasoned statistician who can move comfortably between classical regression techniques and modern Convolutional Neural Networks. The project centres on predictive analytics: you will build, compare and explain regression-based models, explore where a CNN adds value, and present the insights through clear, publication-ready visualisations created in Python (think pandas, scikit-learn, TensorFlow/Keras, matplotlib, seaborn or Plotly—use what fits best). We will begin with a brief video call so I can walk you through the dataset, the business question and the success metrics. After that, you will take full ownership of data preparation, model selection, training, validation and visual storytelling. Expect to hand back clean, well-commented notebooks and graphics that a ...

I need an expert in Python to help with data analysis and processing tasks, specifically focused on unstructured data such as text or images. The ideal candidate should be proficient in Python libraries and tools designed for handling unstructured datasets. Your role will involve creating scripts or sol...analysis and processing tasks, specifically focused on unstructured data such as text or images. The ideal candidate should be proficient in Python libraries and tools designed for handling unstructured datasets. Your role will involve creating scripts or solutions to extract insights, patterns, or other relevant analyses from the data provided. If you have a strong command over libraries like Pandas, NumPy, or specialized tools for text and image processing, I’d love to ...

...inference are a priority. The task breaks down naturally into three parts. First, capture and label representative WLAN traffic—public datasets are fine as a starting point, but I also want a small tool that lets me pipe raw pcap streams into the training set so the system can learn my network's quirks. Second, build and train the detection engine: a well-commented Python project that leverages scapy, pandas, and the scikit-learn implementation of Random Forest, which is my preferred choice for its balance of performance and interpretability. Third, wrap the model in a daemon that watches the interface, raises an alert (syslog plus a webhook) when an attack pattern is scored above the chosen threshold, and writes a short JSON report for later forensics. Deliverables ...

I need an experienced Python trading-bot developer to optimize and refactor a live async trading bot connected to REST & WebSocket APIs, which currently slows under load and misses ticks/orders. The task includes profiling bottlenecks, improving async/WebSocket performance, optimizing pandas & SQLite usage, and ensuring real-time execution. Goal: <200 ms tick-to-order latency, zero missed ticks, clean refactored code, tests, and one-command VPS setup.

...Bluedart but missing a Credit Note in Tally. Cash Flow Forecasting: An AI-driven projection of upcoming payouts vs. vendor liabilities based on Tally’s Ledger. Automated Alerts: Daily WhatsApp/Email snapshots of "Net Profit" and "High-Value Pendency." Technical Requirements: Deep expertise in TallyPrime XML/ODBC interface and Tally API. Strong experience with Power BI, Tableau, or Python (Pandas) for financial data processing. Familiarity with Shopify API and Bluedart (or similar courier) tracking APIs. Ability to work with Tally on Cloud environments. Understanding of E-commerce accounting (GST, RTO, Marketplace settlements). Project Type: This is a part-time, milestone-based project. We prefer a "Discovery & Architecture" phase f...

...time-series data coming from three different sources—raw CSV uploads, existing relational databases, and live API endpoints. The app should read, clean, and merge these feeds on the fly, then offer clear visual insights through line charts, area charts, and any other plots that make trends, seasonality, and anomalies obvious. Under the hood I expect well-structured, reusable Python code that leans on pandas for manipulation, SQLAlchemy (or similar) for database access, and a lightweight requests layer for the APIs. Caching, session-state handling, and responsive layout controls are important so the interface feels fast even as data volumes grow. Deliverables • Streamlit app folder with modular, commented Python scripts • A config file (YAML or .env) that lets me...

...each session so I can practice and submit my results for feedback. • Clear explanations of Excel techniques (Power Query, pivot tables, data validation) and when they are most efficient compared to other tools. • Guidance on structuring my workflow so future projects scale smoothly. I currently want to concentrate on Excel, but I’m open to eventually exploring other options such as Python (Pandas) or R once the fundamentals are strong, so flexibility is appreciated. Please outline: 1. Your experience teaching or mentoring beginners in Excel data cleaning. 2. A suggested session plan or curriculum outline. 3. How you prefer to share files and track my progress. I value clear communication, actionable feedback, and real examples over theory alone. If you ...

I need an academically rigorous thesis that investigates water-pollution violations across the United States, combining robust data analysis with vivid, well-documented case studies. The core objective is to pinpoint patterns of non-compliance, highlight enforcement gaps, and propose policy-oriented solutions grounded in empirical evidence. ...Clean datasets, code (R, Python, or similar), and any visualisations used to generate results. Acceptance Criteria • Originality check <10 % similarity. • All claims supported by primary or reputable secondary sources. • Data and code reproduce the figures and tables included in the manuscript without modification. Please indicate preferred research tools (e.g., SPSS, Stata, Python/pandas) and an estimated timeli...

...escalate. The core must combine traditional threat-intel techniques with machine-learning pipelines so the system continuously adapts as new data arrives. Here’s what success looks like to me: • A modular data-collection layer that can stream pcap, NetFlow, or similar log formats into a preprocessing engine. • Feature-engineering and model-training code written in Python (feel free to leverage Pandas, scikit-learn, TensorFlow, PyTorch—whatever best suits the task). • A detection component that scores incoming traffic and raises alerts via a simple REST API or CLI output. • Clear documentation covering setup, retraining, and how new data sources—such as endpoint events or social-media threat chatter—could be plugged in later. ...

...ready for downstream analytics. You will receive the source file in CSV (UTF-8) plus a short style guide that shows the exact output I need. Please return the cleaned file and a short change log summarizing the transformations you applied. Accuracy and respect for the original content are crucial; no new data should be introduced or removed. Tools like Excel, Google Sheets, OpenRefine, or Python (pandas) are all fine—use whatever helps you turn this around quickly and reliably....

I keep a single master report in Excel that contains every client’s figures. I need a small, repeatable Python script that will: • read the mast...calculations, • split the rows so each client gets only their own data, • save every subset as an individual Microsoft Excel 97-2003 (.xls) file. With Data Visualization for Analysis Inside every generated file I still want the same conditional formatting and any existing cell-level number/date formats to remain intact, so the look and feel matches the master. Please write clean, well-commented code—pandas plus xlwt/xlrd or any other library that supports the older .xls format is fine—as long as it runs from the command line on Windows. Include a short README and one sample output file so I can confirm...

I need help with a Python exercise focused on data analysis. Key tasks include: - Data cleaning/extraction - Visualization/plotting - Statistical analysis Ideal skills and experience: - Proficiency in Python, especially with libraries like Pandas, NumPy, and Matplotlib - Experience with data cleaning and preparation - Strong data visualization skills - Background in statistical analysis

...analysing it in real time, placing orders, and continuously enforcing risk limits. Core functionality • Automated trade execution driven by a configurable strategy engine • Real-time market analysis with fast data ingestion (websocket or streaming API) • Built-in risk management: position sizing, max draw-down and stop-loss rules Technical notes Python is mandatory; common libraries such as pandas, NumPy, TA-Lib, and asyncio are expected. The code should be clean, modular, and ready to plug into broker APIs like Interactive Brokers, Alpaca, or Tradier. A lightweight front-end (CLI or simple dashboard) for live logs and performance metrics would be ideal. Deliverables 1. Fully-commented Python source code and 2. Strategy configuration file(s) allowing ...

...sound, but under load the bot slows, misses price ticks and occasionally skips orders, so I need a clean performance tune-up and code review. Your task is to comb through the existing modules—order manager, data streamer, and strategy loop—identify the bottlenecks, then fix or refactor as needed so the bot reacts in real time without dropping trades. Expect to work with async I/O, websockets, pandas dataframes and a small SQLite trade log. Deliverables • Refactored, well-commented Python code with any slow sections profiled and optimised • A brief report that explains each change, shows before/after latency benchmarks, and lists test results on both sandbox and live endpoints • Updated and a one-command setup script so I can spin the bot up...

I need a seasoned quantitative developer who can ...months of historical options data shows slippage-adjusted results consistent with manual Iron Condor benchmarks. • Live paper-trading session for one full trading day on NSE NOW executes, adjusts, and exits orders without manual intervention. • Clean, well-commented source code plus a config file so strikes, lot sizes, risk caps, and timings can be tweaked easily. Preferred stack Python with Pandas, NumPy, and a proven NSE NOW API wrapper suits me best, but I’m open to other robust solutions if they interface reliably with NSE NOW and meet exchange compliance. If you have prior experience building Indian options engines and can demonstrate exchange-grade reliability, let’s talk schedules and milestones s...

...time-series data coming from three different sources—raw CSV uploads, existing relational databases, and live API endpoints. The app should read, clean, and merge these feeds on the fly, then offer clear visual insights through line charts, area charts, and any other plots that make trends, seasonality, and anomalies obvious. Under the hood I expect well-structured, reusable Python code that leans on pandas for manipulation, SQLAlchemy (or similar) for database access, and a lightweight requests layer for the APIs. Caching, session-state handling, and responsive layout controls are important so the interface feels fast even as data volumes grow. Deliverables • Streamlit app folder with modular, commented Python scripts • A config file (YAML or .env) that...

제가 보유한 방대한 숫자 데이터를 한눈에 보기 쉽도록 깔끔하게 정리해 주셨으면 합니다. • 데이터 유형: 숫자 데이터만 포함되어 있으며, 파일 여러 개를 통합해야 합니다. • 분량: ‘많음’에 해당할 정도로 큼직한 규모라서 자동화 스크립트(Excel Power Query, Python pandas 등)를 활용해 빠르고 정확하게 처리해 주시면 좋겠습니다. 작업 범위 1. 원본 데이터 수집·통합: 엑셀·CSV·구글시트 등 서로 다른 소스에 흩어진 파일을 하나로 모읍니다. 2. 오류 및 중복 검수: 잘못된 포맷, 누락값, 중복 행을 식별해 수정 또는 제거합니다. 3. 구조화 및 정렬: 분석이나 보고서에 바로 사용할 수 있도록 컬럼 체계와 필터를 일관성 있게 맞춥니다. 4. 최종 산출물: 정리된 마스터 파일(Excel 또는 CSV)과 간단한 정리 규칙 문서. 신청 시 ‘숫자 데이터 정리’와 관련된 경험을 중심으로 알려 주세요. 유사 프로젝트 사례나 사용하셨던 도구, 처리 규모를 공유해 주시면 선정에 큰 도움이 됩니다.

import pandas as pd EXCEL_FILE = "" # ----------------------------- # Create Excel Template # ----------------------------- def create_excel_template(): data = { "Service_ID": [], "Sub_Function": [], "DID": [], "Description": [], "Data": [] } df = (data) df.to_excel(EXCEL_FILE, index=False) print(f"Excel template created: {EXCEL_FILE}") # ----------------------------- # Read and Parse Excel # ----------------------------- def parse_excel(): df = pd.read_excel(EXCEL_FILE) # Remove completely empty rows df = (how="all") # Replace NaN with None df = ((df), None) structured_data = [] for _, row in (): se...

I have a collection of PDFs that need to become a single, reliable Excel file. Af...the real priority is cleaning: fixing any odd characters, aligning column formats, checking for obvious entry errors, and making sure the final sheet is ready for downstream analysis. What you’ll hand over: • An Excel workbook converted from the source PDFs. • A fully cleaned version of that workbook, clearly labelled and free of errors. If you have automated routines (Power Query, Python / pandas, VBA, etc.) that speed the job up, all the better—just let me know what you plan to use. When you respond, point me to similar PDF-to-Excel or data-cleaning work you’ve completed in the past so I can gauge fit quickly. I’ll supply the PDFs and any additional formatting...

AI & Full-Stack Tech Client Acquisition Partner Needed (Commission-Based) I am an experienced Full-Stack AI & Software Engineer with strong hands-on expertise in building production-ready systems, including: AI / LLM Development (OpenAI, Gemini, LangChain, RAG, AI Agents) Machine Learning & Data Science (Python, Pandas, NumPy, Scikit-learn) Backend Development (Python, Node.js, REST APIs) MERN Stack (MongoDB, Express, React, Node.js) DevOps & Deployment (Docker, CI/CD, Cloud hosting) Automation & AI Chatbots (WhatsApp, Web, CRM integrations) I deliver scalable, high-quality solutions with clear communication and on-time execution. Role: Client Acquisition Partner I’m looking for a motivated, reliable partner who can bring genuine AI / software developme...

I’m looking for a data scientist based anywhere in Latin America to help me create reliable predictive models for a finance-focused project. You’ll start with large historical datasets stored in SQL and deliver models that accurately forecast key financial indicators. I work mainly with Python, so you’ll find Pandas, NumPy, Scikit-learn and, when deep learning is justified, TensorFlow already in place. If you prefer R for certain tasks, that’s perfectly fine as long as the final workflow remains reproducible. The end-user needs to consume insights through Power BI, so once the model is validated I’ll ask you to craft intuitive dashboards that highlight drivers, confidence ranges and any red-flag anomalies the model detects. Solid statistical grounding ...

...structured e-commerce dataset sitting in Excel/CSV format that needs a thorough exploratory data analysis. My goal is to turn raw tables into an insightful visual narrative—clear charts, concise commentary, and an executive-style report or interactive dashboard that highlights the key patterns hiding in the numbers. Here is what I need from you: • A clean, well-documented analysis (Python with pandas, seaborn/matplotlib or R tidyverse are fine) that walks through data profiling, outlier handling, and any necessary feature engineering. • Compelling visualizations—think sales trends, category performance, customer behaviour—that can be dropped straight into a slide deck or shared as an interactive report (Tableau, Power BI, or a notebook with embedde...

...collection and interpretation practices; second, shaping the core algorithms that will power the software. We’ll be working with the classic trio of techniques—Time Domain, Frequency Domain, and Envelope Analysis—so please be comfortable explaining best-practice workflows and translating them into practical code logic. I already have sample datasets and a basic development environment (Python + NumPy/Pandas/Matplotlib), but I’m flexible if you prefer other analysis libraries such as SciPy or MATLAB. Deliverables • Live or recorded coaching sessions walking through proper sensor placement, sampling parameters, and data cleansing • Annotated pseudo-code or prototype functions that implement the three analysis techniques, ready for integration...

...including product and engineering • Mentor junior AI engineers and contribute to technical leadership • Conduct research and implement state-of-the-art AI techniques • Ensure data quality, security, and model performance optimization Required Skills & Qualifications: • 10+ years of experience in AI/ML or Software Engineering roles • Strong proficiency in Python and data processing libraries (NumPy, Pandas) • Hands-on experience with TensorFlow, PyTorch, Scikit-learn • Strong understanding of Deep Learning, NLP, Computer Vision • Experience with Model Deployment & MLOps pipelines • Experience working with Cloud platforms (AWS / Azure / GCP) • Strong knowledge of Data Engineering & Big Data tools • Experience with ...

...interfaccia web. • Riconoscimento automatico dei fogli e delle colonne numeriche. • Selezione multipla delle colonne da analizzare. • Calcolo e visualizzazione della deviazione standard per ogni colonna scelta, con risultato immediato a schermo. Preferenze tecniche (ma resto aperto a proposte migliori) • Backend in Python con Flask o Django, oppure Node.js. • Librerie consigliate: pandas, NumPy o equivalenti per il calcolo statistico. • Front-end semplice e responsivo, anche con Bootstrap. Consegna 1. Codice sorgente completo e commentato. 2. Istruzioni di installazione (README) per avvio locale. 3. Breve guida utente che spieghi come caricare il file e leggere i risultati. Se puoi offrire anche un piccolo deploy di test (H...

...hours—no end-of-day batching. I code in Python myself, so please keep the architecture transparent: well-named modules, docstrings, and a that pins every dependency. Back-tests on at least two years of 5-minute data, a walk-forward validation segment, and a short README outlining how to reproduce the results will be my acceptance criteria. If you already have experience with pandas, NumPy, scikit-learn or TensorFlow, and you know how to talk to Indian broker APIs via REST or websockets, this should feel familiar. Let me know the models or reinforcement-learning frameworks you think best suit intraday equity trading and how you will protect against over-fitting....

...includes individual customer DGR sheets as separate attachments; the body should recap the overall allocation, while each attachment should show the customer’s own figures. • Retain every day’s data so that, at month-end, I can run a one-click reconciliation against the SLDC meter download and export the results for finance. Tech stack is up to you, yet it must remain readily maintainable—Python/Pandas + PostgreSQL + React or a comparable combo is fine. What matters is that the system eliminates our current manual steps, delivers 200× faster processing, and protects monthly revenue through error-free tracking. Acceptance will be based on: 1. Successful automatic import and validation of a sample QCA schedule. 2. Immediate discrepancy alert whe...

...comparison shows no noticeable deviation. 3. Files open without errors in the latest desktop version of Microsoft Excel. 4. No stray spaces, line breaks or duplicated rows remain after the import and cleanup. I usually spot-check random pages, so 100 % accuracy is essential—please use the tools you trust most, whether that’s Adobe Acrobat, ABBYY FineReader, Power Query, or scripted Python/Pandas, as long as the final spreadsheets meet the standards above....

...perspective on exploratory analysis, pattern discovery, and interpretation so the insights are both rigorous and clearly actionable. The core task is straightforward: ingest the raw text files I provide, clean and structure them appropriately, then run exploratory and statistical analyses that reveal key themes, sentiment trends, and any significant correlations you uncover. Feel free to use Python with pandas, NumPy, NLTK, spaCy, or other standard NLP and data-analysis libraries—whatever you are most comfortable with as long as the workflow is reproducible. Because I don’t have a hard deadline, quality and clarity matter more than speed. You will deliver: • Well-commented notebooks or scripts that walk through each analysis step • A concise report (PDF...