profile image

Ayat Mohammed

@Ayat_Mohammed

0/200

Learn more about ranks

Profile rank: lablab No-rank

Next rank: lablab Apprentice

10

الأحداث التي تم حضورها

3

التسليمات السابقة

Egypt

1عام الخبرة

ملفات التواصل الاجتماعي

🤝 أفضل المتعاونين

🤓 التقديمات

    Submission image

    In the world of football, one of the most important factors for a team's success is the selection of the starting lineup. The starting eleven players must be chosen judiciously, considering various factors such as individual player performance, form, fitness, and tactical strategy. Traditionally, coaches and managers have relied on their expertise, observations, and gut instincts to make these crucial decisions. However, this manual selection process encounters several challenges and limitations: 1. Complex Decision-Making: Football is a complex game, and picking the best players to start can be tricky because it means thinking about many things. This includes player stats, how they've done in the past, the tactics they'll use, and what the other team is good at and not so good at. Even experienced coaches can find this complexity challenging. 2. Data Overload: Football generates an immense amount of data, from player statistics to team dynamics, injury reports, and opponent analysis. Analyzing and integrating this wide array of data manually is time-consuming and open to human error. 3. Incomplete Information: Coaches frequently have restricted knowledge about players' present conditions, like how tired they are or if they have minor injuries. Overlooking or wrongly evaluating these factors can result in less-than-ideal lineup decision To overcome these challenges and make more informed, objective, and optimized decisions regarding football lineups, the solution lies in leveraging the power of artificial intelligence (AI). By developing a machine learning model that can analyze player statistics comprehensively and in real-time, we can predict and recommend the best possible starting eleven for a given match. This AI-driven approach has the potential to revolutionize football strategy by: - Maximizing Performance. - Adaptability. - Objectivity. -Efficiency.

    Submission image
    Hackathon link

    Nightfall Commando

    is an immersive and adrenaline-pumping zombie survival game that plunges players into a post-apocalyptic world overrun by hordes of the undead. Set in a sprawling, decaying metropolis, the game offers a vast open-world environment teeming with danger and opportunities for resource gathering, base building, and strategic combat. With realistic graphics, intense gameplay, and a compelling storyline, players must navigate treacherous streets, abandoned buildings, and dark alleyways to scavenge for supplies, craft weapons, and form alliances with other survivors. Will you adapt, strategize, and survive in this relentless battle for humanity's last hope, or succumb to the relentless onslaught of the undead? The choice is yours in

    Submission image

    We have crafted a sophisticated web application that harnesses the power of machine learning to predict the outcome of football matches, leveraging comprehensive player statistics. This innovative platform dives deep into the individual performance metrics of players, extracting meaningful patterns and insights to forecast the probability of a team's success. By employing advanced algorithms and predictive modeling, the application transforms raw statistical data into actionable predictions. Users can explore a dynamic interface that visualizes the key factors influencing the predictions, offering a user-friendly experience for both casual enthusiasts and dedicated analysts. The machine learning model undergoes continuous refinement through iterative training, ensuring its adaptability to evolving player dynamics and team strategies. This project not only caters to the fervor of football fans but also serves as a valuable tool for stakeholders, including team managers, sports analysts, and betting professionals. Its predictions can aid strategic decision-making, such as optimizing team compositions, adjusting tactics, or informing betting strategies. The web application stands at the intersection of sports, technology, and data analytics, providing a cutting-edge solution for those seeking a deeper understanding of football outcomes. With its intuitive design and robust predictive capabilities, the platform contributes to the evolving landscape of sports analytics, enhancing the way we approach and appreciate the beautiful game.

👌 الهاكاثونات التي تم حضورها

    Submission image

    هاكاثون مسرعة الذكاء الصناعي التوليدي الجزء الثاني

    🗓️ إنضم إلينا افتراضياً بدءًا من الساعة السادسة مساءً في 31 أغسطس وحتى السادسة مساءً في 2 سبتمبر لبدء رحلة التعلم والتطور. 🚀 استمتع بيومين متكاملين من التعلم العملي. 🤝 يمكنك التواصل مع فريقك الخاص أو الانضمام إلى فريق جديد خلال الهاكاثون. 📚 تمتع بالوصول المجاني الغير محدود إلى نماذج الذكاء الاصطناعي والدروس التعليمية التقنية. 🏆 لا تفوّت الفرصة الذهبية للتأهل لبرنامج "GAIA" لتسريع الشركات الناشئة. ⏩ انضم إلى مجتمع خبراء الذكاء الاصطناعي. ⏳ الأماكن محدودة جدا، كن من الحاضرين السريعين!

    Submission image

    SoundAI هاكاثون

    🎧 أهلاً بك في عالم 🤖 الذكاء الاصطناعي الصوتي في "SoundAI هاكاثون. 🚀 استمتع بتحدي يومين لبناء تطبيقات صوتية ذكية، بدءًا من الساعة 6:00 مساءً 🗓️ بتاريخ 7 سبتمبر وحتى الساعة 6:00 مساءً بتاريخ 9 سبتمبر. 🎛️ استفد من تجربة تفاعلية للتعلم النشط وتحسين مهاراتك في التكنولوجيا الصوتية. 👤👥 الانضمام لفريق جديد أو العمل بمفردك، مرحب به. 🚀 توجد فرصة للتأهل في برنامج "GAIA" للشركات الناشئة. ⌛ الأماكن محدودة جدا، سجل الآن واحجز مقعدك في هذه التجربة التعليمية الرائعة!

    Submission image

    هاكاثون بيئة العمل

    🛠 انضم إلينا لمدة يومين من التعلم العملي والابتكار، حيث ستكتشف كيفية التطور ومواجهة التحديات. 🤝 سواء كنت تمتلك فريقًا أو ترغب في الانضمام إلى فريق جديد، فإن الهاكاثون هو المكان المثالي لتطوير بيئة العمل المثالية. 🏅 الهاكاثون هو بابك إلى برنامج "GAIA" لتسريع الشركات الناشئة. 🚀 إذا كنت تبحث عن تغيير ملموس في بيئة العمل، فهذا الهكاثون مناسب لك. 😅 الأماكن محدودة، لذا كن من الأوائل في التسجيل لهذه الرحلة المثيرة!

📝 الشهادات