Some programming experience Be comfortable with coding in Python Windows/Linux/MAC machine Desire to learn data science Nothing else! It's just you, your computer and your ambition to get started today Nothing else! It's just you, your computer and your ambition to get started today Are you ready to start your path to becoming a Data Scientist or ML Engineer? This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

Pakistan's economy is ranked 26th in the world in terms of purchasing power parity (PPP) and 40th in terms of nominal gross domestic product. Pakistan has a population of approximately 190 million people, making it the world's sixth-largest country, with a nominal GDP per capita of $1,427, ranking 133rd globally. The key sectors of the Pakistani economy are agriculture, mining, industry, automotive, construction, defence, services, and transportation. The IT/ITeS sector is one of Pakistan's fastest-growing industries, accounting for around 1% of the country's GDP ($3.5 billion USD). It has doubled in the last four years, and experts predict a further 100% increase to $7 billion in the next two to four years.

Welcome to Machine Learning: Natural Language Processing in Python (Version 2). This is a massive 4-in-1 course covering: 1) Vector models and text preprocessing methods 2) Probability models and Markov models 3) Machine learning methods 4) Deep learning and neural network methods In part 1, which covers vector models and text preprocessing methods, you will learn about why vectors are so essential in data science and artificial intelligence. You will learn about various techniques for converting text into vectors, such as the CountVectorizer and TF-IDF, and you'll learn the basics of neural embedding methods like word2vec, and GloVe. You'll then apply what you learned for various tasks, such as: Document retrieval / search engine Along the way, you'll also learn important text preprocessing steps, such as tokenization, stemming, and lemmatization. You'll be introduced briefly to classic NLP tasks such as parts-of-speech tagging.

ML from scratch is a student-led tutorial / seminar series initiated by Johannes Bill and others from Jan Drugowitsch Lab at Harvard Medical School. The objective is to teach neuroscience students to learn cutting edge machine learning models by implementing them. I started participating from 2022, and I prepared the tutorial and led a few seminars in it!

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Open AI has trained a neural network to play Minecraft by Video PreTraining (VPT) on a massive unlabeled video dataset of human Minecraft play, while using just a small amount of labeled contractor data. With a bit of fine-tuning, the AI research and deployment company is confident that its model can learn to craft diamond tools, a task that usually takes proficient humans over 20 minutes (24,000 actions). Its model uses the native human interface of keypresses and mouse movements, making it quite general, and represents a step towards general computer-using agents. A spokesperson for the Microsoft-backed firm said: "The internet contains an enormous amount of publicly available videos that we can learn from. You can watch a person make a gorgeous presentation, a digital artist draw a beautiful sunset, and a Minecraft player build an intricate house. However, these videos only provide a record of what happened but not precisely how it was achieved, i.e. you will not know the exact sequence of mouse movements and keys pressed. "If we would like to build large-scale foundation models in these domains as we've done in language with GPT, this lack of action labels poses a new challenge not present in the language domain, where "action labels" are simply the next words in a sentence." In order to utilise the wealth of unlabeled video data available on the internet, Open AI introduces a novel, yet simple, semi-supervised imitation learning method: Video PreTraining (VPT). The team begin by gathering a small dataset from contractors where it records not only their video, but also the actions they took, which in its case are keypresses and mouse movements. With this data the company can train an inverse dynamics model (IDM), which predicts the action being taken at each step in the video. Importantly, the IDM can use past and future information to guess the action at each step. The spokesperson added: "This task is much easier and thus requires far less data than the behavioral cloning task of predicting actions given past video frames only, which requires inferring what the person wants to do and how to accomplish it.

Indonesia is a country with enormous economic potential, which has not gone unnoticed by the international community. Indonesia, the largest economy in Southeast Asia, possesses a variety of qualities that position the country well for advanced economic development. Furthermore, the central government has recently shown significant support for reducing Indonesia's historic reliance on (raw) commodity exports while increasing the importance of the manufacturing industry in the economy. Looking ahead, Indonesia's information and communication technology (ICT) sector have a promising future, since the country is only getting started with IT solutions adoption, leaving plenty of space for expansion. Much of Indonesia's potential has yet to be realised, making the country one of the most promising ICT markets in the future years.

This collaboration will increase diversity in the AI tech space where women have been historically excluded. The Finnish Center for Artificial Intelligence (FCAI) and Women in AI Ethics (WAIE) have announced their partnership to increase diversity and ethics in AI. Both organizations focus on empowering people to solve real-life problems through AI that's designed and deployed in an ethical and trustworthy manner. This alliance will increase representation of diverse voices from the Nordic region in the WAIE directory, an online resource to help recruiters and event organizers find diverse talent, and open up opportunities for these talented women to be recognized through WAIE's highly regarded annual "100 Brilliant Women in AI Ethics" list. This international collaboration will include co-hosting of educational workshops by diverse leaders in the AI ethics space, offering a critical lens for real-world solutions. It will also provide a virtuous cycle of mentorship opportunities for FCAI's faculty as well as students and WAIE's rich network of women as well as non-binary folks who are in all stages of their AI ethics careers to inspire others from marginalized communities to join this important space.

This course offers a deep and wide range of skills set from Programming to statistics and machine learning algorithms. The skills you will attain from this course could make you an expert Data Analyst, Quality Analyst and Business Analyst and Statistical Analyst roles. Machine learning algorithms such as Regression, Clustering, Classification and prominent libraries such as Pandas, Matplotlib, SciKit -learn is covered from this course. The main goal of the course is to provide a deeper understanding and hands-on learning experience on the Data Science domain with the help of Python programming language along with real-time Data Science projects to provide an overall knowledge on Data Science domain. This course covers all the topics from Mathematics to Programming to Visualization techniques that are needed for a Data Scientist role.