The post Best ML Project with Dataset and Source Code appeared first on finnstats. If you are interested to learn more about data science, you can find more articles here finnstats. Best ML Project with Dataset and Source Code, Understanding how machine learning algorithms are applied in practice in business requires an understanding of machine learning projects. These machine learning projects for students will also... If you are interested to learn more about data science, you can find more articles here finnstats. The post Best ML Project with Dataset and Source Code appeared first on finnstats.

Dr. Sachin R Sakhare is working as a Professor in the Department of Computer Engineering of Vishwakarma Institute of Information Technology, Pune, India. He has 26 Years of experience in engineering education. He is recognised as PhD guide by Savitribai Phule Pune University and currently guiding 7 PhD scholars. He is a life member of CSI, ISTE and IAEngg. He has Published 39 research communications in national, international journals and conferences, with around 248 citations and H-index 6.

Artificial intelligence (AI) has been redefining society in ways we've by no means expected. The era is clinging to us in every aspect of our lives, from unlocking our smartphones to our daily sports, online shopping, smart car dashboards, self-sustaining robots, and so on. Moreover The Indian government is also pushing the private sector and offering many opportunities and fields through DSTP, NITI-Aayog, IndiaAi, and many more, to create modern technological answers and fund AI-based start-ups, as Artificial intelligence is the tool of innovation being experimented with in almost all Indian domain names, which includes healthcare, education, agriculture, finance, vehicles, energy, retail, manufacturing, and clinical research with self-sustaining discoveries in the region. Non-fungible tokens are becoming increasingly popular; these tokens have proven a first-rate virtual answer for collectibles. Typically, they replicate diverse real-world factors, which include songs, artwork, movies, and in-sport objects.

Ankit currently works as a Senior Research Scientist at Uber AI Labs, the machine learning research arm of Uber. His work primarily involves the application of Deep Learning methods to a variety of Uber's problems ranging from forecasting, food delivery to self driving cars. Previously, he has worked in variety of data science roles at Bank of America, Facebook and other startups. Additionally, he has been a featured speaker in many of the top AI conferences and universities across US including UC Berkeley, OReilly AI conference etc. He completed his MS from UC Berkeley and BS from IIT Bombay (India).

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we're building the team to help push our shopping cart forward. If you're ready to do the best work of your life, come join our table.

In the AWS Deep Learning Challenge held from January 5, 2022, to March 1, 2022, participants from academia, startups, and enterprise organizations joined to test their skills and train a deep learning model of their choice using Amazon Elastic Compute Cloud (Amazon EC2) DL1 instances and Habana's SynapseAI SDK. The EC2 DL1 instances powered by Gaudi accelerators from Habana Labs, an Intel company, are designed specifically for training deep learning models. Participants were able to realize the significant price/performance benefits that DL1 offers over GPU-based instances. We are excited to announce the winners and showcase some of the machine learning (ML) models that were trained in this hackathon. You will learn about some of the deep learning use cases that are supported by EC2 DL1 instances, including computer vision, natural language processing, and acoustic modeling.

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Picture this, again; you walk into a grocery store, you get the groceries you want, and then walk out. No lines, no payment, just walk out. With it's sensor fusion, computer vision and deep learning technology, Amazon is able to identify you and charge your account, without you having to do anything. You scan your phone via the Amazon app, walk in, shop, and then leave. In order for this to work, I'll let you figure out what data points you have to give up.

Trigo is a provider of AI & computer vision based checkout-free systems for the retail market, enabling frictionless checkout and a range of other in-store operational and marketing solutions such as predictive inventory management, security and fraud prevention, pricing optimization and event-driven marketing. The system is based on ceiling-mounted off-the-shelf cameras and sensors, powered by proprietary deep learning algorithms, built to map and analyze the location and movement of every object throughout the store. When shoppers pick an item from the shelf, the system automatically detects the event and adds it to a virtual shopping list. Once the shoppers are done, they can simply walk out with no need to go through conventional checkout. Upon leaving the store, customers are charged automatically and the receipt is sent to their mobile device.

Yuxi (Hayden) Liu is a Software Engineer, Machine Learning at Google. Previously he worked as a machine learning scientist in a variety of data-driven domains and applied his ML expertise in computational advertising, marketing and cybersecurity. He is now developing and improving the machine learning models and systems for ads optimization on the largest search engine in the world. He is an author of a series of machine learning books and an education enthusiast. His first book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon in 2017 and 2018, and was translated into many different languages.